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Patent 2368001 Summary

Third-party information liability

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Claims and Abstract availability

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(12) Patent Application: (11) CA 2368001
(54) English Title: SYSTEM AND METHOD FOR GATHERING DATA FROM WIRELESS COMMUNICATIONS NETWORKS
(54) French Title: SYSTEME ET PROCEDE PERMETTANT DE COLLECTER DES DONNEES A PARTIR DE RESEAUX DE RADIOCOMMUNICATION
Status: Dead
Bibliographic Data
(51) International Patent Classification (IPC):
  • H04W 24/00 (2009.01)
  • H04W 4/02 (2009.01)
  • H04W 16/02 (2009.01)
(72) Inventors :
  • FRANGIONE, TOM (United States of America)
  • HEIDOHRN, MARK (United States of America)
  • OYLER, JOHN (United States of America)
  • PEYRAT, ALAN (United States of America)
(73) Owners :
  • TELEPHIA, INC. (United States of America)
(71) Applicants :
  • TELEPHIA, INC. (United States of America)
(74) Agent: BORDEN LADNER GERVAIS LLP
(74) Associate agent:
(45) Issued:
(86) PCT Filing Date: 2000-03-14
(87) Open to Public Inspection: 2000-09-21
Examination requested: 2003-05-21
Availability of licence: N/A
(25) Language of filing: English

Patent Cooperation Treaty (PCT): Yes
(86) PCT Filing Number: PCT/US2000/006652
(87) International Publication Number: WO2000/056098
(85) National Entry: 2001-09-14

(30) Application Priority Data:
Application No. Country/Territory Date
09/271,105 United States of America 1999-03-17
09/392,012 United States of America 1999-09-08

Abstracts

English Abstract




A system and method for gathering data from wireless communication networks,
the wireless communication network including a plurality of cell sites, mobile
subscriber units, and a mobile telephone switching office. The data gathering
system comprises a plurality of data gathering nodes and a control center.
Each data gathering node comprises multiple receivers, with each receiver
gathering data from a different wireless communication network. Stored data at
the control center is processed to generate marketing information on each
wireless communication network.


French Abstract

Système et procédé permettant de collecter des données à partir de réseaux de radiocommunication comprenant une pluralité de stations cellulaires, des unités d'abonnés mobiles et un centre de commutation de téléphones mobiles. Le système de collecte de données comprend une pluralité de noeuds de collecte de données et un centre de commande. Chaque noeud de collecte de données comprend de multiples récepteurs, dont chacun collecte les données provenant d'un réseau de radiocommunication différent. Les données mises en mémoire au niveau du centre de commande sont traitées de façon à générer des renseignements à caractère commercial sur chacun des réseaux.

Claims

Note: Claims are shown in the official language in which they were submitted.



CLAIMS
1. A system for gathering data from a plurality of wireless communication
networks, said
system comprising:
a plurality of data gathering nodes, each data gathering node of said
plurality of data
gathering nodes comprising;
an antenna system; and
a plurality of receivers tuned to gather data from the plurality of wireless
communication networks, each receiver of said plurality of receivers
coupled to said antenna; and
a control center coupled to said plurality of data gathering nodes, said
control center
processing data received from said plurality of data gathering nodes.
2. The system of claim 1 wherein each data gathering node of said plurality of
data
gathering nodes further comprises a local processor and storage device,
coupled to said
plurality of receivers.
3. The system of claim 1 further comprising a network linkage coupled between
said
plurality of receivers and said control center, said network linkage sending
stored data
from said plurality of receivers to said control center.
4. The system of claim 3 wherein said network linkage comprises a modem.
5. The system of claim 1 wherein said plurality of receivers comprise N
receivers, where
N is an integer greater than one and equal to the number of wireless
communication
networks from which data is being gathered, and wherein each receiver at a
data
gathering node gathers data from a wireless communication network that is
different
from other wireless communication networks from which data is gathered by
other
receivers of said data gathering node.


6. The system of claim 1 wherein the control center further comprises a
relational
database for storing data gathered by said plurality of data gathering nodes.
7. The system of claim 6 wherein said relational database utilizes event type,
cell location,
market location, carrier location, and frequency band relational tables to
cross-reference
index value meanings in a user information table for each event.
8. The system of claim 1 further comprising an offline storage media for
archiving and
backup of the data gathered by said plurality of data gathering nodes.
9. The system of claim 1 further comprising a data mining application that
processes the
data gathered by said plurality of data gathering nodes to produce marketing
and usage
characterization information useful for wireless communication network service
providers to determine their relative strengths and weaknesses to other
wireless
communication network service providers.
10. The system of claim 9 wherein said marketing and usage characterization
information
produced comprises information on subscriber share, call share, number of new
subscribers, and number of churning subscribers for each wireless
communication
network of the plurality of wireless communication networks.
11. The system of claim 1, wherein said control center transmits instructions
modifying
receiver data gathering settings to each receiver of said plurality of
receivers.
12. In a plurality of wireless communication networks, each wireless
communication
network of said plurality of wireless communication networks comprising a
layout of
cell sites divided into location areas that overlap the cell layout of each
other wireless
communication network in a given geographic area, the system of claim 1
wherein:
at least one data gathering node of said plurality of data gathering nodes is
placed in
a different location area of each wireless communication network of said
plurality
of wireless communication networks allowing it to gather data from a group of
cell
sites; and
41




each data gathering node gathers data for a time period from a first cell in a
cell
group of each wireless communication network, then gathers data for a time
period
from a second cell in a cell group of each wireless communication network, and
then gathers data for a time period from each cell in a cell group of each
wireless
communication network until data has been gathered for all cells in a cell
group of
each wireless communication network.

13. The system of claim 1 wherein said data gathering nodes are fixed,
transportable, or a
combination of fixed and transportable.

14. The system of claim 1 wherein each receiver of said plurality of receivers
encrypts
portions of the data gathered by each receiver of said plurality of receivers
into unique
subscriber identifiers to protect subscriber identities.

15. The system of claim 1 wherein each receiver of said plurality of receivers
generates a
unique subscriber identifier for each different subscriber from the RF
fingerprint of the
signal received.

16. The system of claim 1 wherein each receiver of said plurality of receivers
filters the
data that said receiver has gathered to remove private or extraneous data
before sending
the data to said control center.

17. The system of claim 2 wherein said local processor encrypts portions of
the data
gathered by said plurality of receivers into unique subscriber identifiers
prior to storage
at said storage device.

18. A system for gathering data from a plurality of wireless communication
networks, said
system comprising:
A means for gathering data from a plurality of geographic locations in a
plurality of
wireless communication networks, said means comprising;
means for receiving electromagnetic energy at each cell group of said
plurality of cell groups; and



42


means for gathering data from a plurality of wireless communication
networks at each cell group of said plurality of cell groups; and
means for storing the data gathered from said plurality of geographic
locations.
19. The system of claim 18 further comprising a means for processing the data
gathered
from said plurality of geographic locations to produce marketing and usage
characterization information.
20. A method for gathering data from a plurality of wireless communication
networks
comprising the steps of:
deploying a plurality of data gathering nodes at various geographic locations
in a
plurality of wireless communication networks;
gathering data at said plurality of data gathering nodes from each wireless
communication network of said plurality of wireless communication networks;
and
processing the data at a control center.
21. The method of claim 20, wherein said step of processing the data at a
control center
comprises eliminating redundant pages to the same subscriber to reduce storage
space
and analysis processing time.
22. The method of claim 21 wherein eliminating redundant pages to the same
subscriber
comprises the steps:
sorting through the gathered data from said plurality of data gathering nodes;
identifying pages to a same subscriber occurring within a pre-determined time
period from each other; and
eliminating all of said pages except one.
43


23. The method of claim 20 further comprising the step of using a data mining
application
to process the data gathered by said plurality of data gathering nodes to
produce
marketing and usage characterization information.
24. The method of claim 20, wherein said step of deploying a plurality of data
gathering
nodes at various geographic locations in a plurality of wireless communication
networks comprises the steps of placing at least one data gathering node of
said
plurality of data gathering nodes in each location area of each wireless
communication
network of said plurality of wireless communication networks.
25. The method of claim 24, wherein said step of gathering data at said
plurality of data
gathering nodes comprises the step of at each data gathering node of said
plurality of
data gathering nodes, simultaneously gathering data from each location area of
each
wireless communication network of said plurality of wireless communication
networks.
26. The method of claim 24, wherein said step of gathering data at said
plurality of data
gathering nodes comprises the steps of:
at each data gathering node of said plurality of data gathering nodes,
employing a
sampling algorithm to gather data from a cell group of each wireless
communication network of said plurality of wireless communication networks;
and
simultaneously employing said sampling algorithm at all data gathering nodes
of
said plurality of data gathering nodes to gather data from each location area
of said
plurality of wireless communication networks.
27. The method of claim 26, wherein said sampling algorithm to gather data
from a cell
group of each wireless communication network, comprising the steps of:
monitoring the channel assignment of a first cell base station for a time
period for
each wireless communication network;
changing the monitoring frequency to monitor the channel assignment of a
second
cell base station for a time period for each wireless communication network;
and
44


changing the monitoring frequency to monitor the channel assignment of the
base
station of each of N cells for a time period for each wireless communication
network, where N equals the number of cells in each cell group of the data
gathering node and is not necessarily equal for each wireless communication
network.
28. The method of claim 20, wherein all of the cells of said plurality of
wireless
communication networks is sampled.
29. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises calculating the share
of
subscribers for each wireless communication network for a given time period.
30. The method of claim 29, wherein said method of calculating the share of
subscribers for
each wireless communication network of said plurality of wireless
communication
networks for a given time period comprises:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and counting a base number
of
different unique subscriber identifiers for each wireless communication
network of
said plurality of wireless communication networks;
extrapolating the base number of different unique subscriber identifiers for
each
wireless communication network to an adjusted number of unique subscriber
identifiers;
summing the number of adjusted unique subscriber identifiers counted for each
wireless communication network of said plurality of wireless communication
networks to produce a total number of subscribers for said plurality of
wireless
communication networks; and
dividing the number of adjusted unique subscriber identifiers for each
wireless
communication network of said plurality of wireless communication networks by


said total number of subscribers for said plurality of wireless communication
networks.
31. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises calculating the number
of new
subscribers each wireless communication network added during a given time
period.
32. The method of claim 31, wherein said step of calculating the number of new
subscribers for each wireless communication network added during a given time
period
comprises:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and generating a list of
unique
subscriber identifiers;
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during a prior time period and generating a list of
unique
subscriber identifiers;
comparing the list of unique subscriber identifiers for the given time period
to the
prior time period and counting the number of new unique subscriber identifiers
that
appear in the given time period but not the prior time period; and
extrapolating said number of new unique subscriber identifiers to an adjusted
number of new unique subscriber identifiers.
33. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises calculating the number
of
churning subscribers who canceled service for each wireless communication
network
during a given time period.
46




34. The method of claim 33, wherein said step of calculating the number of
churning
subscribers who canceled service for each wireless communication network
during a
given time period comprises:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during a prior time period and generating a list of
unique
subscriber identifiers;
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and generating a list of
unique
subscriber identifiers;
comparing the list of unique subscriber identifiers for the prior time period
to the
given time period and counting the number of churning unique subscriber
identifiers that appear in the prior time period but not the given time
period; and
extrapolating said number of churning subscribers to an adjusted number of
churning subscribers.

35. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises calculating the share
of calls
made by subscribers of each wireless communication network for a given time
period.

36. The method of claim 35, wherein said step of calculating the share of
subscriber calls
made for each wireless communication network for a given time period
comprises:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and counting the number of
traffic channel assignments made by each wireless communication network of
said
plurality of wireless communication networks;



47


extrapolating said number of counted traffic channel assignments to a total
number
of subscriber calls for the given time period for each wireless communication
network;
summing the total number of subscriber calls extrapolated for the given time
period
for each wireless communication network of said plurality of wireless
communication networks to produce a total number of subscribers calls for said
plurality of wireless communication networks; and
dividing said total number of subscriber calls for each wireless communication
network of said plurality of wireless communication networks by said total
number
of calls for said plurality of wireless communication networks.
37. The method of claim 36 wherein the number of traffic channel assignments
counted
does not include traffic channel assignments made to roaming subscribers.
38. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises calculating the share
of
roamers of each wireless communication network for a given time period.
39. The method of claim 38, wherein said step of calculating the share of
roamers for each
wireless communication network for a given time period comprises:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and counting a base number
of
roamers for each wireless communication network of said plurality of wireless
communication networks;
extrapolating the base number of roamers for each wireless communication
network
to an adjusted number of roamers;
48




summing the number of adjusted roamers for each wireless communication
network of said plurality of wireless communication networks to produce a
total
number of roamers for said plurality of wireless communication networks; and
dividing the adjusted number of roamers for each wireless communication
network
of said plurality of wireless communication networks by said total number of
subscribers for said plurality of wireless communication networks.

40. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises profiling the quality
of
subscribers for each wireless communication network.

41. The method of claim 40 wherein said type of subscribers comprise new,
churning, and
base subscribers.

42. The method of claim 40, wherein said step of profiling the quality of
subscribers for
each wireless communication network for a given time period comprises:
sorting through the data gathered from each data gathering node and
identifying the
different unique subscriber identifiers corresponding to the type of
subscriber to be
profiled for each wireless communication network;
counting the number of traffic channel assignments made to each said unique
subscriber identifier;
counting the total number of said different unique subscriber identifiers for
all
wireless communication networks;



49


dividing said total number for all wireless communication networks into
subunits
according to the number of traffic channel assignments made; and
for each subunit, calculating the market share percentage of number of
subscribers
for each wireless communication network in the subunit.
43. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises calculating the share
of calls
for each wireless communication network during a given time period.
44. The method of claim 43, wherein said step of calculating the share of
calls for each
wireless communication network during a given time period comprises:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and counting a base number
of
traffic channel assignments made for each wireless communication network of
said
plurality of wireless communication networks during a given time period;
extrapolating the base number of traffic channel assignments for each wireless
communication network during said time period to an adjusted number traffic
channel assignments;
summing the number of adjusted traffic channel assignments during said time
period for each wireless communication network of said plurality of wireless
communication networks to produce a total number of traffic channel
assignments
during said period for said plurality of wireless communication networks; and
dividing the adjusted number of traffic channel assignments during said time
period
for each wireless communication network of said plurality of wireless
communication networks by said total number of traffic channel assignments for
said plurality of wireless communication networks.


45. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises calculating the share
of
incoming and outgoing calls for each wireless communication network.
46. The method of claim 45, wherein said step of calculating the share of
incoming and
outgoing calls for each wireless communication network during a given time
period
comprises:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes and identifying each traffic channel assignment for each
wireless communication network of said plurality of wireless communication
networks;
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes and identifying each page for each wireless communication
network of said plurality of wireless communication networks;
identifying which traffic channel assignments are incoming calls by sorting
through
said traffic channel assignments and pages and identifying which traffic
channel
assignments are immediately preceded by a page to the same subscriber.
counting a base number of incoming calls for each wireless communication
network
of said plurality of wireless communication networks by counting the number of
traffic channel assignments immediately preceded by a page to the same
subscriber;
counting a base number of outgoing calls for each wireless communication
network
of said plurality of wireless communication networks by counting the number of
traffic channel assignments not immediately preceded by a page to the same
subscriber
extrapolating the base number of incoming and outgoing calls for each wireless
communication network to an adjusted number of incoming and outgoing calls;
51


summing the number of incoming calls for each wireless communication network
of said plurality of wireless communication networks to produce a total number
of
incoming calls for said plurality of wireless communication networks;
dividing the adjusted number of incoming calls for each wireless communication
network of said plurality of wireless communication networks by said total
number
of incoming calls for said plurality of wireless communication networks.
summing the number of outgoing calls for each wireless communication network
of
said plurality of wireless communication networks to produce a total number of
outgoing calls for said plurality of wireless communication networks;
dividing the adjusted number of outgoing calls for each wireless communication
network of said plurality of wireless communication networks by said total
number
of outgoing calls for said plurality of wireless communication networks.
47. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises identifying dual mode
subscribers of analog and wireless communication networks operated by the same
service provider.
48. The method of claim 47, wherein said step of identifying dual mode
subscribers of
analog and wireless communication networks operated by the same service
provider
comprises:
sorting through the data gathered from a service provider analog wireless
communication network and identifying traffic channel assignments;
sorting through the data gathered from said service provider digital wireless
communication network and identifying traffic channel assignments; and
52


identifying traffic channel assignments made to the same subscriber appearing
in
both the analog and digital wireless communication networks.
49. The method of claim 23, wherein said step of processing the data at said
control center
to produce marketing information on each wireless communication network of
said
plurality of wireless communication networks comprises identifying new
subscribers of
a wireless communication network who are churning subscribers from a different
wireless communication network.
50. The method of claim 49, wherein said step of identifying new subscribers
of a wireless
communication network who are churning subscribers from a different wireless
communication network comprises:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and generating a list of
unique
subscriber identifiers;
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during a prior time period and generating a list of
unique
subscriber identifiers;
comparing the list of unique subscriber identifiers for the given time period
to the
prior time period and identifying the new unique subscriber identifiers that
appear
in the given time period but not the prior time period; and
comparing said new unique subscriber identifiers to a list of unique
subscriber
identifiers for each different wireless communication network and identifying
which said unique subscriber identifiers appear on said list of unique
subscriber
identifiers of a different wireless communication network.
51. A method for gathering data at a data gathering node comprising the steps
of:
scanning readable control channels and their corresponding cell site
identification;
53


measuring the approximate signal strength of each control channel;
deciding which channels of said readable control channels data will be
gathered
from; and
gathering data from said channels.
52. A method for processing a data file gathered from a plurality of wireless
communication networks to calculate the share of subscribers for each wireless
communication network for a given time period, said method comprising the
steps of:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and counting a base number
of
different unique subscriber identifiers for each wireless communication
network of
said plurality of wireless communication networks;
extrapolating the base number of different unique subscriber identifiers for
each
wireless communication network to an adjusted number of unique subscriber
identifiers;
summing the number of adjusted unique subscriber identifiers counted for each
wireless communication network of said plurality of wireless communication
networks to produce a total number of subscribers for said plurality of
wireless
communication networks; and
dividing the number of adjusted unique subscriber identifiers for each
wireless
communication network of said plurality of wireless communication networks by
said total number of subscribers for said plurality of wireless communication
networks.
53. A method for processing a data file gathered from a plurality of wireless
communication networks to calculate the number of new subscribers each
wireless
54


communication network added during a given time period, said method comprising
the
steps of:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and generating a list of
unique
subscriber identifiers;
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during a prior time period and generating a list of
unique
subscriber identifiers;
comparing the list of unique subscriber identifiers for the given time period
to the
prior time period and counting the number of new unique subscriber identifiers
that
appear in the given time period but not the prior time period; and
extrapolating said number of new unique subscriber identifiers to an adjusted
number of new unique subscriber identifiers.
54. A method for processing a data file gathered from a plurality of wireless
communication networks to calculate the number of churning subscribers who
canceled
service for each wireless communication network during a given time period,
said
method comprising the steps of:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during a prior time period and generating a list of
unique
subscriber identifiers;
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and generating a list of
unique
subscriber identifiers;
comparing the list of unique subscriber identifiers for the prior time period
to the
given time period and counting the number of churning unique subscriber
identifiers that appear in the prior time period but not the given time
period; and


extrapolating said number of churning subscribers to an adjusted number of
churning subscribers.
55. A method for processing a data file gathered from a plurality of wireless
communication networks to calculate the share of subscriber calls made for
each
wireless communication network for a given time period, said method comprising
the
steps of:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and counting the number of
traffic channel assignments made by each wireless communication network of
said
plurality of wireless communication networks;
extrapolating said number of counted traffic channel assignments to a total
number
of subscriber calls for the given time period for each wireless communication
network;
summing the total number of subscriber calls extrapolated for the given time
period
for each wireless communication network of said plurality of wireless
communication networks to produce a total number of subscribers calls for said
plurality of wireless communication networks; and
dividing said total number of subscriber calls for each wireless communication
network of said plurality of wireless communication networks by said total
number -
of calls for said plurality of wireless communication networks.
56. A method for processing a data file gathered from a plurality of wireless
communication networks to calculate the share of roamers for each wireless
communication network for a given time period, said method comprising the
steps of:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and counting a base number
of
56


roamers for each wireless communication network of said plurality of wireless
communication networks;
extrapolating the base number of roamers for each wireless communication
network
to an adjusted number of roamers;
summing the number of adjusted roamers for each wireless communication
network of said plurality of wireless communication networks to produce a
total
number of roamers for said plurality of wireless communication networks; and
dividing the adjusted number of roamers for each wireless communication
network
of said plurality of wireless communication networks by said total number of
subscribers for said plurality of wireless communication networks.
57. A method for processing a data file gathered from a plurality of wireless
communication networks to profile the quality of subscribers for each wireless
communication network for a given time period, said method comprising the
steps of:
sorting through the data gathered from each data gathering node and
identifying the
different unique subscriber identifiers corresponding to the type of
subscriber to be
profiled for each wireless communication network;
counting the number of traffic channel assignments made to each said unique
subscriber identifier;
counting the total number of said different unique subscriber identifiers for
all
wireless communication networks;
dividing said total number for all wireless communication networks into
subunits
according to the number of traffic channel assignments made; and
for each subunit, calculating the market share percentage of number of
subscribers
for each wireless communication network in the subunit.
57


58. The method of claim 57 wherein said type of subscribers comprise new,
churning, and
base subscribers.
59. A method for processing a data file gathered from a plurality of wireless
communication networks to calculate the share of calls for each wireless
communication network during a given time period, said method comprising the
steps
of:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes and counting a base number of traffic channel assignments
made for each wireless communication network of said plurality of wireless
communication networks during a given time period;
extrapolating the base number of traffic channel assignments for each wireless
communication network during said time period to an adjusted number traffic
channel assignments;
summing the number of adjusted traffic channel assignments during said time
period for each wireless communication network of said plurality of wireless
communication networks to produce a total number of traffic channel
assignments
during said period for said plurality of wireless communication networks; and
dividing the adjusted number of traffic channel assignments during said time
period
for each wireless communication network of said plurality of wireless
communication networks by said total number of traffic channel assignments for
said plurality of wireless communication networks.
60. A method for processing a data file gathered from a plurality of wireless
communication networks to determine whether traffic channel assignments
correspond
to incoming or outgoing calls, said method comprising the steps of:
58


sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes and identifying each traffic channel assignment for each
wireless communication network of said plurality of wireless communication
networks;
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes and identifying each page for each wireless communication
network of said plurality of wireless communication networks; and
identifying which traffic channel assignments are incoming calls by sorting
through
said traffic channel assignments and pages and identifying which traffic
channel
assignments are immediately preceded by a page to the same subscriber.
61. A method for processing a data file gathered from a plurality of wireless
communication networks to calculate the share of incoming and outgoing calls
for each
wireless communication network, said method comprising the steps of:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes and identifying each traffic channel assignment for each
wireless communication network of said plurality of wireless communication
networks;
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes and identifying each page for each wireless communication
network of said plurality of wireless communication networks;
identifying which traffic channel assignments are incoming calls by sorting
through
said traffic channel assignments and pages and identifying which traffic
channel
assignments are immediately preceded by a page to the same subscriber;
counting a base number of incoming calls for each wireless communication
network
of said plurality of wireless communication networks by counting the number of
traffic channel assignments immediately preceded by a page to the same
subscriber;
59


counting a base number of outgoing calls for each wireless communication
network
of said plurality of wireless communication networks by counting the number of
traffic channel assignments not immediately preceded by a page to the same
subscriber;
extrapolating the base number of incoming and outgoing calls for each wireless
communication network to an adjusted number of incoming and outgoing calls;
summing the number of incoming calls for each wireless communication network
of said plurality of wireless communication networks to produce a total number
of
incoming calls for said plurality of wireless communication networks;
dividing the adjusted number of incoming calls for each wireless communication
network of said plurality of wireless communication networks by said total
number
of incoming calls for said plurality of wireless communication networks;
summing the number of outgoing calls far each wireless communication network
of
said plurality of wireless communication networks to produce a total number of
outgoing calls for said plurality of wireless communication networks; and
dividing the adjusted number of outgoing calls for each wireless communication
network of said plurality of wireless communication networks by said total
number
of outgoing calls for said plurality of wireless communication networks.
62. A method for identifying new subscribers of a wireless communication
network
who are churning subscribers from a different wireless communication network,
said
method comprising the steps of:
sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during the given time period and generating a list of
unique
subscriber identifiers;
60


sorting through the data gathered from each data gathering node of said
plurality of
data gathering nodes during a prior time period and generating a list of
unique
subscriber identifiers;
comparing the list of unique subscriber identifiers for the given time period
to the
prior time period and identifying the new unique subscriber identifiers that
appear
in the given time period but not the prior time period; and
comparing said new unique subscriber identifiers to a list of unique
subscriber
identifiers for each different wireless communication network and identifying
which said unique subscriber identifiers appear on said list of unique
subscriber
identifiers of a different wireless communication network.
63. A method for identifying dual mode subscribers of analog and wireless
communication networks operated by the same service provider, comprising the
steps
of:
sorting through the data gathered from a service provider analog wireless
communication network and identifying traffic channel assignments;
sorting through the data gathered from said service provider digital wireless
communication network and identifying traffic channel assignments; and
identifying traffic channel assignments made to a same subscriber appearing in
both
the analog and digital wireless communication networks.
61

Description

Note: Descriptions are shown in the official language in which they were submitted.




CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
SYSTEM AND METHOD FOR GATHERING DATA FROM WIRELESS
COMMUNICATIONS NETWORKS
Inventors: Tom Frangione, Mark Heidohrn, John Oyler, Alan Peyrat
RELATED U.S. APPLICATION DATA
Continuation-in-part of Ser. No. USSN 09/271,105, March 17, 1999.
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates generally to data gathering systems and, in particular,
to
systems and related methods for simultaneously gathering data from multiple
wireless
communication networks.
2. Description of the Related Art
The basic structure and operation of wireless communication networks,
including
cellular, paging, wireless local loop, and satellite communication networks
are well known.
A typical cellular communication network essentially consists of a plurality
of mobile
subscriber units (MSUs), a plurality of cell sites with base station
equipment, a plurality of_
base station controllers (BSCs), which may be associated with each base
station, or may be
centralized to provide control for a plurality of base stations, a mobile
telephone switching
office (MTSO or Mobile Switching Center (MSC)) and various local or networked
databases which may include a home location register (HLR), visitor location
register
(VLR), authentication center (AuC) and equipment identity register (EIR).



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A typical cellular communication network is characterized by the concepts of
frequency reuse and handof~ In some cellular systems, a frequency is reused at
many sites
which are geographically separated from each other by a distance sufficient to
ensure that
the interference from other sites utilizing the same frequency is low enough
to permit a
quality signal from the primary serving site. Handoffs are the process of
changing the
serving site as a subscriber moves from the primary service area of one site
to that of
another.
Ordinarily, cellular systems are initially designed with a set of cell sites
that provide
partial overlapping RF coverage over a market area of interest. In order to
provide
increased capacity, additional cell sites are constructed between the initial
cell sites. The
coverage area of each cell site is reduced through a combination of antenna
system design
and transmitter power reduction in order to provide limited overlap of
individual coverage
areas while maintaining contiguous coverage. In some cellular systems,
capacity within
each cell is limited by the available spectrum and the number of frequency
assignments that
can be assigned for that cell without violating the interference constraints
of the common
air interface standard employed for the network. Capacity can also be reused
through the
use of "sectored" sites, in which a single site is equipped with antenna
systems and
transceivers to permit multiple cells to be created from a single site. A
common sectoring
approach utilizes three sectors per site, each providing primary coverage in a
different
120°-wide sector around the site, while partially overlapping with the
other two sectors.
Common frequency reuse patterns range from a reuse pattern of twenty-one, in
which the
frequency assignments are reused over a pattern of seven tri-sectored sites in
Frequency
Division Multiple Access (FDMA) systems, to reuse patterns of one, in which
the same
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frequency assignment is reused in every cell in Code Division Multiple Access
(CDMA)
systems.
There are various common air interface (CAI) standards that are used in the
radio
communications link between the MSU and the cell site. The earliest type in
common use
is known as Frequency Division Multiple Access (FDMA), in which each
communications
channel consists of a single narrowband carrier, generally employing analog
frequency
modulation. Digital systems generally provide multiple communications channels
within a
single frequency assignment. In Time Division Multiple Access (TDMA) systems,
a
carrier is modulated with a binary signal, with channels cyclically assigned
to unique
timeslots. The number of channels available for a carrier frequency assignment
varies with
the particular TDMA standard, typically ranging from three to eight with
current full rate
vocoders. Another type of digital modulation in common use, Code Division
Multiple
Access (CDMA), typically differentiates up to sixty-four spread spectrum
modulation
channels using orthogonal spreading codes within a single wideband frequency
assignment.
Channels that are transmitted from the base stations and received by MSUs are
known as forward channels, while those that are transmitted from the MSU and
received by
the base station are known as reverse channels. Channels are further
differentiated by their
function. Those that are generally used for signaling between the MSU and the
base station
are known as control channels, while those that are generally used to carry
voice or data
signals are known as traffic channels. Generally, some limited forms of
signaling are
available when a call is in progress on a traffic channel to permit control of
the call in
progress or to support system requirements such as handoffs.



CA 02368001 2001-09-14
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In certain cellular systems, when an MSU is in an idle mode, it may select a
forward
control channel (FCC) to monitor for signaling information. If the MSU is
required to
transmit information to the base station, it will do so on a corresponding
reverse control
channel (RCC). The protocols for the various common air interfaces determine
which
FCC-RCC pair is to be used. FCCs are used to send two types of messages.
Overhead
messages provide information to all MSU units monitoring the channel, and may
include
system and cell site identifiers, and information regarding the system
configuration (e.g.
neighbor lists). The FCC also provides information for specific users,
including pages
and short data messages. Absent any means of determining which cell is being
monitored
by a particular MSU, such messages would need to be broadcast over all the
FCCs of all
cells within a network in order to ensure that the MSU receives the message.
This is
practical in smaller systems, but in systems with more than a few tens of
thousands of
subscribers, it is desirable to subdivide the network into location areas
(LAs) in order to
avoid exceeding the data throughput capacity of the FCC. Subscriber messages
can then be
I S broadcast through the FCC of all the cells in the LA in which the MSU is
monitoring a
FCC.
Cellular systems ordinarily use a process known as registration in order to
determine which LA serves a MSU. Generally, when an MSU is first turned on, it
will
initially monitor the strongest available FCC. It will then register in
accordance with
information contained within the FCC overhead data. This is accomplished by
exchanging
prescribed messages, including the subscriber identity, over the FCC-RCC pair.
The VLR
stores the information regarding the most current LA is then stored in the
system VLR and
the MSU. If the MSU later determines that the LA identifier included in the
FCC no longer
matches the data it has stored, it will initiate a location update that will
repeat the
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registration process with the new LA identifier. Re-registration may also
occur in response
to system requests. In systems in which LAs are utilized, subscriber messages
are initially
sent only to cells within the system which correspond to the LA information
for the MSU
that is stored in the VLR.
Generally, when a call is made to a registered MSU, the network sends a page
from
the base station to the MSU by broadcasting a paging message on the FCC of the
cells
within the LA. If received, the MSU responds by sending its identifying
information once
again to the network along with a message confirming that it received the
page. The
network then sends a traffic channel assignment to the MSU on the forward
control
channel.
Ordinarily, when an MSU originates a call, the MSU initiates a signaling
sequence
which includes its identity and the called number using the RCC that
corresponds to the
monitored FCC. After verifying that the MSU corresponds to a valid subscriber
record, the
MSU is assigned to a traffic channel and the MTSO completes the call to the
called
number.
For a given geographic area, there are typically several competing service
providers
operating wireless communication networks. Each will have certain licensed
frequency
assignments, or bands of licensed frequencies, that it is permitted to use
within its network.
Each will have a common air interface, generally an industry standard, but
occasionally a
proprietary system developed by a particular vendor and not subjected to an
industry
standards process.
In the past, equipment has been developed to test the operation of, and
characterize
the quality of, the individual networks. Test equipment has been developed
that allow the
5



CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
simultaneous testing of multiple networks at a single location. When coupled
with
navigation and data recording and analysis capabilities, they permit
characterizing the
comparative quality of various networks over a given set of geographical
points, one
location at a time (generally referred to as a drive route, since the test
equipment is
ordinarily installed in a vehicle and driven throughout a market area.)
However, such equipment typically is limited to gathering information from the
portions of the networks that are in the vicinity of the test equipment. In
major cellular
system market area, this may mean the equipment is limited to gathering
information from
a small subset of the active cells at any given moment in time. In addition,
since a purpose
of the equipment is to test the operation and the quality of the wireless
communication
networks, the data processing capabilities of such equipment generally are not
designed to
gather data to make market share, usage comparisons, or user profiles for the
different
wireless communication networks.
Current methods of gathering information about subjects such as market share,
usage, and user profile data often have been limited to telephone surveys,
generally
conducted by telemarketing research firms. This type of information is
critical to wireless
communications operators, who may expend significant resources on advertising
and
promotions to attract customers and need metrics to judge the effectiveness of
these
expenditures. But the accuracy and reliability of such telephone surveys
sometimes is
limited as they provide only anecdotal data and may use an insufficient
statistical sample.
Furthermore, in some cases these methods result in unsolicited charges to
wireless
customers. As a result, there has been a need for more comprehensive data
gathering
systems and related methods for gathering marketing information about wireless
communication networks.
6



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SUMMARY OF THE INVENTION
The present invention encompasses data gathering systems and related methods
for
gathering data from wireless communication networks. For a given geographic
area, there
may be several service providers operating wireless communication networks
utilizing
various types of common air interface standards. One data gathering system in
accordance
with the invention gathers data from each wireless communication network
simultaneously.
The system comprises a plurality of data gathering nodes deployed in a
sampling network,
and a control center that provides management of the data collection processes
of each
node, data collection from each of the nodes, error detection, management of
the collected
I O data, and overall administration of the network.
A data gathering node may comprise multiple receivers, a minimum of one for
each
wireless communication network. Each receiver employs a sampling algorithm to
gather
data from cell sites surrounding the data gathering node. The data gathered
from each data
gathering node is periodically sent to a control center. where it is stored.
I 5 Later, a data mining application may be run on the gathered data to
generate
marketing and usage information for each of the wireless communication
networks.
The present invention is explained in more detail below with reference to the
drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
20 Figure I is an illustrative block diagram of a data gathering system for
wireless
communication networks in accordance with a presently preferred embodiment of
the
invention.
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WO 00/56098 PCT/US00/06652
Figure 2 is a representation of a cell layout of a wireless communication
network
and shows the placement of data gathering nodes like the one in Figure 4
Figure 3 is a representation of a group of cell sites comprising a cell group
from
which a data gathering node of Figure 4 samples to gather data.
Figure 4 is a block diagram of the presently preferred embodiment of one of
the
data gathering nodes of the system of Figure 1.
Figure 5 is a representation of storage of the gathered data in a relational
database.
Figure 6 is a sample excerpt of a baselining period data file.
Figure 7 is a sample excerpt of a data file from which marketing and usage
characterization information is to be generated.
Figure 8 is a comparison between actual subscribers and measured subscribers
used
in calculating the subscriber share gross-up coefficient.
Figure 9 is a sort of the data found in Figure 7 to count the number of
measured
subscribers.
Figure 10 shows the calculation of the subscriber share gross-up coefficients
and the
market share percentage of each wireless communication network.
Figure 11 is a sample report containing information on subscriber share.
Figure 12 is a sample excerpt of a second data file from which marketing and
usage
characterization information is to be generated.



CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
Figure 13 is a comparison of different subscribers between the data file shown
in
Figure 7 and a second data file shown in Figure 12 used to determine new and
churning
subscribers.
Figure 14 shows the calculation of the new subscriber gross-up coefficients
and the
market share percentage of new subscribers for each wireless communication
network.
Figure 15 shows the calculation of the churning subscriber gross-up
coefficients and
the market share percentage of churning subscribers for each wireless
communication
network.
Figure 16 is a sample report containing information on new subscribers.
Figure 17 is a sample report containing information on churning subscribers.
Figure 18 is a comparison of actual roamers to roamers measured during a
baseline
period used to calculate the roamer gross-up coefficient.
Figure 19 is a data sort of the data file of Figure 7 counting the number of
roamers.
Figure 20 shows the calculation of the roamer gross-up coefficient and the
share of
roamers for each wireless communication network.
Figure 21 is a sample report containing information on roamer share.
Figure 22 is a comparison of actual calls and measured calls during a baseline
period used to calculate the call share gross-up coefficient.
Figure 23 is a data sort of the file in Figure 7 counting the number of
traffic channel
assignments made for each wireless communication network.



CA 02368001 2001-09-14
WO 00156098 PCT/US00/06652
Figure 24 shows the calculation of the call share gross-up coefficient and the
call
share for each wireless communication network.
Figure 25 is a sample report containing information on call share.
Figure 26 is a sample excerpt of a data file from which base subscriber
profiling
information is to be generated.
Figure 27 is a data sort of the file shown in Figure 26 to identify the number
of
traffic channel assignments made to different subscribers.
Figure 28 is a data sort of the file shown in Figure 27 arranging subscribers
by
number of traffic channel assignments.
Figure 29 is a data sort of the file shown in Figure 28 dividing the data into
quartiles
and counting the number of subscribers for each wireless communication network
in each
quartile.
Figure 30 shows the calculation of market share of base subscribers for each
wireless communication network in each quartile.
Figures 31 and 32 are sample excerpts of data files from which new and
churning
subscriber profiling information is to be generated.
Figure 33 is a data sort of the files shown in Figures 31 and 32 identifying
new and
churning subscribers.
Figure 34 is a data sort of the file in Figure 31 counting the number of
traffic
channel assignments made to new subscribers.



CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
Figure 35 is a data sort of Figure 34 arranging subscribers by number of
traffic
channel assignments.
Figure 36 is a data sort of the file shown in Figure 35 dividing the data into
quartiles
and counting the number of new subscribers for each wireless communication
network in
each quartile.
Figure 37 shows the calculation of market share of new subscribers for each
wireless communication network for each quartile.
Figure 38 shows a data sort of Figure 31 counting the number of traffic
channel
assignments made to churning subscribers.
Figure 39 is a data sort of Figure 38 arranging churning subscribers by the
number
of traffic channel assignments made.
Figure 40 is a data sort of the file shown in Figure 39 dividing the data into
quartiles
and counting the number of churning subscribers for each wireless
communication network
in each quartile.
1 S Figure 41 shows the calculation of market share of churning subscribers
for each
wireless communication network for each quartile.
Figure 42 is a sample excerpt of a data file from which peak and non-peak call
share
information is to be generated.
Figure 43 is a comparison between actual calls and measured calls during a
baseline
period used to calculate the peak/non-peak call share gross-up coefficient.
11



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Figure 44 is a data sort of the file in Figure 42 counting the number of
traffic
channel assignments made during peak and non-peak hours for each wireless
communication network.
Figure 45 shows the calculation of the peak/non-peak gross-up coefficient and
the
peak and non-peak call share for each wireless communication network.
Figure 46 is a sample excerpt of a data file from which incoming and outgoing
call
information is to be generated.
Figure 47 is a data sort of the file in Figure 46 identifying traffic channel
assignments and pages for each wireless communication network.
Figure 48 shows the processing of the file shown in Figure 48 to identify and
count
incoming and outgoing calls.
Figure 49 shows the calculation of the ingoing/outgoing call share gross-up
coefficient and the incoming and outgoing call share for each wireless
communication
network.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
The present invention encompasses data gathering systems and related methods
for
gathering data from wireless communication networks. The following description
is
presented to enable any person skilled in the art to make and use the
invention, and is
provided in the context of a particular application and its requirements.
Various
modifications to the preferred embodiment will be readily apparent to those
skilled in the
art, and the generic principles defined herein may be applied to other
embodiments and
applications without departing from the spirit and scope of the invention.
Thus, the present
12



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invention is not intended to be limited to the embodiment shown, but is to be
accorded the
widest scope consistent with the principles and features disclosed herein.
A block diagram of a presently preferred embodiment of a data gathering system
for
wireless communication networks is shown in Figure 1. In a presently preferred
embodiment of the invention, the data gathering system comprises N data
gathering nodes
( 110) placed at various locations in a geographic area served by wireless
communication
networks, where N is an integer greater than one and represents the number of
data
gathering nodes used to gather data from cell sites in the wireless
communication networks.
Each data gathering node is coupled to a control center (120).
Referring to Figure 2, a sample wireless communication network is represented
by a
distribution of cell sites (210) throughout a geographic area. The density of
all sites (210)
is greater in areas of high wireless communication traffic. The placement of
each data
gathering node (220) is dependent on the cell layouts of the wireless
communication
networks. A survey may be conducted prior to selecting monitoring locations in
order to
provide useful information regarding the density of cell sites (210) and the
approximate
areas the cell sites serve. Data gathering nodes (220) are placed in locations
that permit
each data gathering node to monitor an approximately equal number of cell
sites (210) in
each network and, in aggregate, maximize the number of cell sites (210) of
each network
that are monitored. Typically, in areas with greater cell densities, data
gathering nodes
(220) are spaced more closely together and locations are selected which have a
smaller area
in which they can effectively monitor cell sites.
Typically, cells within a wireless communication network are associated with
location areas (230) which are defined by the network operator. In the
preferred
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embodiment, at least one data gathering node (220) is placed within each
location area
(230) of each wireless communication network to "sample" or gather data from
the group
of cell sites surrounding the data gathering node (a "cell group"). Data
gathering nodes
(220), either transportable or fixed, may also be deployed within each
location area (230) to
gather data from additional cell sites (210) depending on the quantity and
density of cell
sites (210) within a particular location area (230) in order to gain
sufficient samples of
subscriber messages.
Factors affecting the cell sites (210) from which a data gathering node can
gather
data include the physical environment of the node (particularly its height
above the local
terrain and the physical structures in the immediate vicinity of its antenna
network), the
relative locations and orientations of the local cell site antennas, the
transmit power of the
cells, and the terrain and morphology between the node and cell locations. The
data
gathering nodes (220) that are initially placed based on the cell layouts and
location areas
are meant to remain fixed for an extended period of time, although some
initial adjustment
may be necessary to optimize the gathering of data from the most number of
cell sites (210)
by each data gathering node from each wireless communication network. Periodic
adjustments may be required in response to ongoing changes in the monitored
networks.
When the data gathering nodes (220) are initially placed, particular attention
is paid to
ensure that data is gathered from all cell sites in high usage areas such as
business centers,
high traffic areas, or airports and bridges.
As shown in Figure 4, each node may have multiple receivers, each configured
to
monitor control channels of base stations of one of multiple cellular
networks. Prior to
performing monitoring operations, each receiver is programmed to undertake an
initialization process in which it scans all of the appropriate control
channels of the wireless
14



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communication network that it is monitoring. The local processor will create
and maintain
a record of all readable control channels, their corresponding cell
identifiers (or other
information that may permit distinguishing the control channel of once cell
site from that of
another), location area identifiers, and the approximate received signal
strength of each.
This information will be uploaded to the control center (120), which then
determines which
data gathering nodes (220) are responsible for monitoring which cell sites
(210).
The control center will develop a set of sampling plans based upon the system
configuration data. In the preferred embodiment, groups of cells for each
network will be
designated as within the sampling plan of a data gathering node based upon the
following
objectives and constraints: (1) all cells within a group will be within the
same location area,
(2) the number of cells in each group will be the same, (3) the levels of
subscriber messages
will be the same in each group, (4) the signal levels from each cell within
the group will
exceed a designated CAI-dependent threshold, and (5) the sampling plan will be
consistent
with the configuration of the data gathering node. The development of the
sampling plan
may be performed manually, or may be accomplished automatically using an
optimization
program or process that provides a optimal solution using assigned weighting
factors for
each objectives, while maintaining location area and data gathering node
configuration
constraints.
Figure 3 shows a grouping of cell sites of one cellular system surrounding a
data
gathering node (310) that is monitored by one of the receivers of node (310)
in accordance
with a presently preferred embodiment of the invention. Although a cell group
for only one
wireless communication network is shown, each data gathering node will sample
from cell
groups for each wireless communication network in a similar manner. The data
gathering
node (310) samples signals transmitted from a base station in cell site (320)
for a time



CA 02368001 2001-09-14
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period, and then samples signals transmitted from the base station in cell
site (330) for a
time period, followed by cell site (340), cell site (350), cell site (360),
cell site (370), and
finally cell site (380). The data gathering node (310) samples signals from
base stations
belonging to each wireless communication network.
Once all of the cell sites of a cellular system that are associated with the
data
gathering node have been sampled, the sampling process is then repeated again
starting
with cell site (320). The data gathering node monitors signals transmitted
from the base
station in a new cell by switching to the corresponding channel assignment of
the base
station in the new cell. In the preferred embodiment, a data gathering node
will gather data
from several seconds to several minutes from each cell in the cell group
(230). The time
periods may be uniform for each cell, or may be weighted based upon historical
rates of
subscriber messages monitored from each cell site. Other factors affecting the
sampling
period include the wireless communication network from which data is being
gathered, and
the strength at the data gathering node of the signal from the cell being
monitored. In an
alternative embodiment, each data gathering node does not sample each cell in
the group of
cell sites, but rather only a single cell site.
Referring to Figure 4, a block diagram of the presently preferred embodiment
of the
data gathering node of the system of Figure 1 is shown. Each data gathering
node
comprises an antenna network (410) that comprises one or more antennas and an
RF
distribution network connecting the antennas) to the receivers (420), P
receivers (420),
where P is an integer greater than one and represents the number of forward
control
channels from which data is to be gathered, a local processor with
capabilities similar to a
personal computer (440), a local storage device such as a hard drive (445),
and a modem
(450). Currently there typically are between six and eight wireless
communication
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networks in each major market. Some common air interface standards utilize
more than
one forward control cannel in a cell site, thus requiring more than one
receiver per wireless
communication network.
The antenna network (410) is coupled to each receiver (420) for signal
reception,
and each receiver (420) includes a corresponding controller (430). The
combination of
receivers at each data gathering node (110) is capable of receiving and
decoding traffic
from any common air interface standard on which a particular service provider
may be
operating, including N/AMPS (Narrowband/Advanced Mobile Phone Service), TDMA
(Time Division Multiple Access), CDMA (Code Division Multiple Access), GSM
(Global
System for Mobile telephones), and iDEN in the cellular, SMR and PCS frequency
bands.
Each receiver (420) is coupled to the local processor (440). Each controller
(430) allows
the local processor (440) to control its corresponding receiver (420)
functions, such as
channel selection, decode mode, and cell sampling patterns. Each receiver is
capable of
receiving a forward control channel (FCC), forward traffic channel (FTC),
reverse control
channel (RCC), and reverse traffic channel (RTC) signals of a cellular
communication
network, determining the approximate received signal strength for the channel,
and either
decoding the signaling data or determining the presence of traffic.
It is the task of the receivers to process the incoming radio signals into
useful
information by demodulating the signals and decoding the raw data into useful
information
according to the particular cellular communication standard being used. In the
presently
preferred embodiment, each receiver (420) monitors the forward control
channels of a
different wireless communication network, observing all messages broadcast by
the base
station sent to all MSUs in the cell site associated with the service provider
of interest.
Different receivers can be configured to receive information compliant with
N/A~IPS
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(Narrowband/Advanced Mobile Phone Service), TDMA (Time Division Multiple
Access),
CDMA (Code Division Multiple Access), GSM (Global System for Mobile
telephones),
and iDEN in the cellular, SMR and PCS frequency bands. In alternative
embodiments,
each receiver (420) may monitor a reverse control channel, forward traffic
channel, or
reverse traffic channel of a different wireless communication network.
Messages decoded
from the reverse control channel can be processed to generate subscriber
calling pattern
information as well as subscriber identity information, as further described
below.
Demodulation and decoding of the forward control channel signal yields the
messages transmitted over the forward control channel, as well as filler data,
repeated
messages, and checksum data. Filler data, repeated messages, and checksum data
are
generally filtered out and discarded by the receiver to facilitate data
handling, leaving only
formatted messages. In the presently preferred embodiment, each receiver (420)
selects the
following messages to save and discards all other messages: (1) certain
overhead messages
that provide system and cell site identification, network quality information
(e.g. busy/idle
bit), and registration instructions, (2) Registration Confirmations, which
include the
subscriber MIN being confirmed, time of day and date of the confirmation, base
station
identification, and frequency/carrier identifier, (3) Pages, which include the
subscriber MIN
being paged, and (4) Traffic channel assignments, which include the subscriber
MIN for
which a channel is being assigned.
The filtered messages are then sent to the local processor (440) which records
the
time of receipt of each message. The local processor (440) is comparable in
capabilities to
a desktop personal computer. The local processor (440) is equipped with a
fault tolerant
power supply of sufficient dimension and capabilities to assure immunity to
short duration
power interruptions and the ability to shut down and restart in the event of a
prolonged
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power outage. The local processor (440), based upon data processing commands
received
from the control center ( 120), may further filter messages. Messages are
accumulated in
temporary memory (RAM) in block files associated with the forward control
channels
associated with each receiver. Certain fields in the messages, such as
portions of the
subscriber MIN, are encrypted into unique subscriber identifier numbers that
correlate to a
specific subscriber using standard public/private key algorithms such as DES
or MDS.
Portions of the MIN corresponding to the area code are not encrypted into the
unique
subscriber identifier in order to gather data on roamers. Each data gathering
node (110)
will use the same public key to encrypt the MIN to simplify key management.
The
corresponding private key is held in escrow, and is unavailable to be used to
decrypt the
unique subscriber identifiers, thus protecting the privacy of subscribers. In
an alternative
embodiment, subscriber MINS are encrypted into unique subscriber identifiers
at the
receivers (440) rather than the local processor (440). At no time is an
unencrypted MIN
stored on a permanent media vulnerable to security breaches.
On a periodic basis, or whenever the forward control channel monitoring
assignment is changed, the block file associated with the forward control
channel is closed,
compressed using a standard compression format such as ZIP to minimize storage
and
transmission requirements, and sent to a local storage device (445) such as a
hard drive
where it is appended to a file corresponding to its associated wireless
communication
network. A new block file is created which corresponds to the next block time
period and
forward control channel.
Alternatives exist to using MINs to generate unique subscriber identifiers. In
one
alternative embodiment, each receiver (420) monitors the reverse control
channel as well as
the forward control channel. Demodulation and decoding of the reverse control
channel
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signal yields a message corresponding to the ESN of the MSU. In this
alternative
embodiment, the ESN is encrypted to produce a unique subscriber identifier
rather than the
MIN gathered from the forward control channel. In another alternative
embodiment, the
unique RF wave pattern (RF fingerprint) transmitted by each MSU on the reverse
control
channel is used to assign a different unique subscriber identifier to each RF
fingerprint. In
these alternative embodiments, the messages pertaining to the MINs gathered
from the
forward control channel are filtered out with the extraneous information
rather than
encrypted.
On a scheduled basis, all files are closed and prepared for uploading to the
control
center (120). A file header is created for each wireless communication network
file that
summarizes the statistics of the corresponding file, including peg counts for
each type of
message recorded and a summary of any apparent alarm conditions or system
outages
detected during the reporting period. The control center (120) initiates a
dialup routine to
connect with the local processor (440), which sends the data file containing
data gathered
since the previous dialup. Alternatively, the local processor (440) may
initiate the
communications session based upon previously downloaded instructions and
schedules
from the control center (120). In alternative embodiments, the connection
between the
control center (120) and the local processor (440) can be made via the
Internet, an RF link,
or a wide area network.
The control center ( 120) may also initiate a dialup routine to connect with
the local
processor (440) at other times to transmit any revised settings for the
receivers to the local
processor (440), such as frequency selection or sampling patterns. The local
processor
(440) will then transmit changes to the controller (430) at each receiver
(420). In the
preferred embodiment, the control center (120) initiates a dialup routine once
a day, at



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which time the local processor (440) sends the data file containing data
gathered since the
previous dialup and the control center ( 120) transmits any revised settings
for the receivers
to the local processor (440). In the preferred embodiment, the dialup linkage
occurs
landline via a standard telephone modem (450), but in an alternative
embodiment the dialup
linkage may be wireless.
At the control center (120), each data file received from a data gathering
node is
decompressed and the data file is error checked to ensure data integrity. This
includes
examining the timestamps of the first and last event in the data file and
confirming that the
data file is composed of data gathered during the expected time period since
the previous
data upload. Second, messages are sampled from the data file and compared to
the
messages in the corresponding positions in the previous day's data to confirm
that the
messages are not identical to the previous day's data. In an alternative
embodiment,
instead of error checking the data file against only the prior day's data
file, the data file can
be error checked against several previous days of data collected to ensure
that new data has
been collected. In the preferred embodiment, the first message, last message,
and eight
messages at equal intervals between the first and last messages are sampled,
for a total of
ten sampled messages.
The data file is also checked to ensure that receivers have been functioning
properly
and gathering data throughout the collection period. Data files collected from
previous
collection periods are used to generate a normal range of occurrences for each
type of
message over a given collection period. After the data file is downloaded, the
control
center ( 120) counts the number of occurrences of each type of message and
ensures that the
numbers fall within the expected normal range of each type of message.
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After the uploaded data files from all the data gathering nodes ( 110) have
been error
checked, they are processed to generate a single file of messages. Since data
is gathered
from multiple data gathering nodes simultaneously, there may be undesired
duplicate
entries for the same event. This is particularly the case when multiple data
gathering nodes
are monitoring cells within the same location area. Since, for the purposes of
the presently
preferred embodiment, the desired data is that a particular MSU received a
page at a
particular time, redundant page signals attempting to locate the MSU are
undesirable and
eliminated. The elimination of redundant pages significantly reduces both the
space
required to store the gathered data and the query time required when
aggregating and
analyzing the data.
To eliminate redundant pages, the control center (120) sorts through all of
the data
files received from each data gathering node (110) and identifies pages to the
same
subscriber that were received at different data gathering nodes (110) within a
pre-
determined window of time and selects the page with the earliest time stamp.
The control
center ( 120) then eliminates all other pages to the same subscriber within
the pre-
determined window of time. The pre-determined window of time may vary
depending on
the wireless communication network standard from which the data is gathered,
and may be
refined from time to time based on prior data that has been gathered.
Once the data files from each data gathering node (110) are processed into a
single
file of overhead messages, pages, traffic channel assignments, and
registration events, this
file is processed for storage in a relational database at the control center
(120). A
representation of the storage format for gathered data is shown in Figure 5. A
userinformation table (510) is created for each event containing fields on the
event date and
time, area code of the subscriber, cell site location, event type, market
frequency band, and
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carrier. Information pertaining to the event type, cell site location, market,
frequency band,
and carrier fields is represented in the userinformation table (510) by an
indexed numerical
value, with a corresponding relational table for cross-referencing each
indexed numerical
value with a text description of its meaning.
Each type of event is designated an index value in the userinformation table
(510),
with a related eventType table (520) cross-referencing the index value with
the type of
event (page, traffic channel assignment, registrations). Similarly, the cell
site location of
the event is designated an index value, with a relational cellinformation
table (530) cross-
referencing the index value with a text description of the cell site
locations.
Market, carrier, and frequency band information is allocated a single field in
the
userinformation table (510) and is designated a single index value. This index
value is
designated by a marketFrequency table (540), which contains individual fields
for market,
carrier, and frequency band information. The market is designated an index
value in the
marketFrequency table (540), with a relational market table (550) cross-
referencing each
index value with a text description of the corresponding market. Similarly,
both the carrier
and frequency band are each designated an index value in the marketFrequency
table (540),
with a relational Carrier table (550) and frequencyBand table (560) cross-
referencing the
index values with a text description of the corresponding carrier and
frequency band.
All new data files received from all data gathering nodes (110) are backed up
and
archived on a regularly scheduled basis using the standard commercial features
of a
database management system. Standard archiving procedures are used to back up
to an
offline storage media such as magnetic tape or CD-ROM, which are then stored
in a secure,
fireproof safe.
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A data mining application is run on the data file to aggregate and analyze the
data to
produce summary tables and reports. The format of a sample table is shown in
Figure 5. A
user table (570) identifies each unique subscriber identification number and
keeps track of
the date the unique subscriber identification number first appeared and the
date it last
appeared. The user table (570) is updated each time a new file is processed.
In the
preferred embodiment, the data mining application is run at the control center
(120). In an
alternative embodiment, the data mining application can access the control
center remotely
to aggregate and analyze the data file stored at the control center ( 120).
The data mining
application generates periodic reports (monthly in the preferred embodiment)
containing
marketing and usage characterization information useful to wireless
communication
network service providers, wireless equipment manufacturers, service
retailers, consultants,
and financial institutions. Reports and gathered data can be provided through
web-based
access (including real time displays of data being gathered), e-mail delivery,
electronic data
delivery, or hard print. In the presently preferred embodiment, such
information comprises
the share of subscribers relative to other wireless communication networks,
the number of
new subscribers, the number of churning subscribers (subscribers who have
dropped their
service), and the share of total calls made by subscribers of a wireless
communication
network relative to subscribers of other wireless communication networks, the
number and
share of roamers for each wireless communication network, profiling of the
quality of new;
existing, and churning subscribers for each wireless communication network
based upon
the share of subscriber calls made, share of calls during peak and non-peak
hours for each
wireless communication network, and share of incoming and outgoing calls for
each
wireless communication network.
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In alternative embodiments, the data mining application may generate other
types of
marketing and usage characterization information, such as subscriber usage
characteristics
with respect to items such as number, time and location of calls made and
received for each
service provider, and use the number of gross adds for a wireless
communication network
following media advertising or special promotional pricing plans as a basis to
track the
impact and effectiveness of such advertising or special promotions. It is
recognized that
the data mining application can process the data files to generate many other
types of
marketing and usage characterization information similar to those described
herein.
Figures 6 and 7 are sample excerpts of information contained in the data files
stored
at the control center (120) for illustration of how the data mining
application generates
information on market share of subscribers for each wireless communication
network, the
number and share of new subscribers and churning subscribers, the number and
share of
roamers, and share of total calls made by subscribers. Only data for two
wireless
communication networks is shown, but a complete file will have data for all
wireless
communication networks.
Figure 6 represents excerpts of data files containing data taken during a
baseline
period. This baseline period raw data is compared to actual data received from
service
providers for the time period corresponding to the baseline period to
determine how much
data was missed by the data gathering system. Figure 7 is a sample excerpt of
a data file at
the control center (120) that the data mining application is to analyze to
generate marketing
and usage characterization information.
The data mining application calculates the subscriber share for each wireless
communication network by first generating a subscriber share gross-up
coefficient that



CA 02368001 2001-09-14
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accounts for data that is missed by the data gathering nodes (120). The data
mining
application sorts through the baselining period data and generates a list of
different
subscriber identifiers that are contained in the baselining period data. These
different
subscriber identifiers are compared to a list of actual subscriber identifiers
generated from
information received from service providers to determine how many subscribers
the data
gathering nodes missed. The comparison of these two lists is shown in Figure
8. Figure 10
shows one method for calculating the subscriber share gross-up coefficient for
each
wireless communication network. The actual number of subscribers during the
baseline
period is divided by the number of measured subscribers during the baseline
period.
Alternatively, more comprehensive standard statistical methods can be used to
calculate
gross-up coefficients. The data gathering nodes will miss subscriber
identifiers because not
all of the cells in the wireless communication network are monitored
simultaneously and
continuously. As a result, for example, an event may have started and ended in
a cell
before being recorded. However, this base number of subscribers approximates
the actual
number of subscribers because as the number of recorded events increases, the
number of
unique subscriber identifier numbers grows asymptotically to the actual level.
Although a
particular event may be missed, the more data that is recorded in the future,
the more likely
future events involving the same unique subscriber identifiers may be
recorded. Only one
record is required to identify that a subscriber is active. Where the data
collection period is
a month, a sufficient number of events have been recorded to approach this
asymptotic
level. These additional factors may be taken into account when generating the
gross-up
coefficients for each wireless communication network.
To determine the share of subscribers for each wireless communication network,
the
data mining application sorts the data file and counts the number of different
subscriber
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identifiers for each wireless communication network. Figure 9 is the result of
such a sort of
the file shown in Figure 7. The number of subscribers counted for each
wireless
communication network is multiplied by the corresponding subscriber share
gross-up
coefficient to generate an extrapolated number of subscribers for each
wireless
communication network. The market share of each wireless communication network
is
then generated by dividing the extrapolated number of subscribers for each
wireless
communication network by the total number of extrapolated subscribers for all
wireless
communication networks. Figure 10 shows the extrapolation of the number of
subscribers
counted for each wireless communication network shown in Figure 9 and the
calculation of
the subscriber share for each wireless communication network. A sample report
containing
information on subscriber share over a monthly period is shown in Figure 11.
Figure 12 is a sample excerpt of data for a particular time period in which it
is
desired to determine the number of new and churning subscribers since a prior
collection
period. The data mining application calculates the number of new subscribers
added by
over a particular time period by each wireless communication network by
comparing a list
of unique subscriber identifiers of the particular time period to a list of
unique subscriber
identifiers of a prior time period and counting the number of unique
subscriber identifiers
that do not appear in the prior period. Similarly, the number of churning
subscribers for
each wireless communication network who discontinued their service at the end
of a prior
time period is calculated by comparing a list of the unique subscriber
identifiers of the
particular time period to a list of unique subscriber identifiers of the prior
time period and
counting the number of unique subscriber identifiers that appear in the prior
time period,
but not the particular time period. Figure 13 shows this process for a list of
unique
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subscriber identifiers sorted from a prior time period data file shown in
Figure 7 and a list
of unique subscriber identifiers from the particular time period shown in
Figure 12.
The number of new subscribers for each wireless communication network counted
in Figure 13 is multiplied by a corresponding new subscriber gross-up
coefficient to
generate an extrapolated number of new subscribers for each wireless
communication
network. The new subscriber gross-up coefficient can be calculated in many
ways. In the
presently preferred embodiment, the subscriber share gross-up coefficient
calculated
previously is used since the number of new subscribers missed by the data
gathering nodes
is proportional to the number of subscribers missed. The share of new
subscribers for each
wireless communication network is calculated by dividing the extrapolated
number of new
subscribers for each wireless communication network by the total number of
extrapolated
subscribers for all wireless communication networks. Figure 14 shows the
extrapolation of
the number of new subscribers counted for each wireless communication network
shown in
Figure 13 and the calculation of the new subscriber share for each wireless
communication
network.
Identifying the new subscribers for each wireless communication network can
also
be used to track subscribers who have left one service provider for another
once Local
Number Portability is mandated in the year 2001. Under Local Number
Portability,
subscribers can keep their MIN when switching from one service provider to
another. To
identify a subscriber who switched from one service provider to another, for
each new
subscriber, the data mining application sorts through the list of unique
subscriber identifiers
for each other service provider to see if the new unique subscriber identifier
appears
previously as a subscriber to a different service provider. If so, this
subscriber is identified
as a subscriber who has switched from another service provider. In this
manner,ahe data
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mining application can generate reports on the number of subscribers who
switched from
one service provider to another, and which service providers lost and gained
subscribers
from which other service providers.
The ability to track new subscribers and new subscribers coming from other
service
providers can also be used to quantify the effectiveness of media campaigns by
service
providers, such as tracking the increase in subscribers per advertising dollar
spent, relative
effectiveness of television, radio, and print medium advertisements, and
effectiveness of
particular types of promotional plans, such as free air time or lack of
roaming charges.
The same process for calculating share of new subscribers for each wireless
communication network is followed for calculating the share of churning
subscribers
counted in Figure 13. Figure 15 shows the extrapolation of the number of
churning
subscribers counted for each wireless communication network shown in Figure 13
and the
calculation of the churning subscriber share for each wireless communication
network.
Figures 16 and 17 show sample reports containing information an new and
churning
subscribers over a monthly period.
The data mining application calculates the roamer share for each wireless
communication network by first generating a roamer gross-up coefficient that
accounts for
data that is missed by the data gathering nodes (120). The data mining
application sorts
through the baseline period raw data shown in Figure 6 and generates a list of
roamers by
identifying area codes outside the wireless communication network for which
data is being
gathered. This list of roamers is compared to a list of actual roamers
generated from
information received from service providers to determine how many roamers the
data
gathering nodes missed. The comparison of these two lists is shown in Figure
18. A
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roamer gross-up coefficient is calculated by dividing the number of actual
roamers by the
measured number of roamers. The calculation of the roamer gross-up coefficient
from the
data in Figure 18 is shown in Figure 20.
The data mining application calculates the number and share of roamers over a
particular period for each wireless communication network by sorting the data
file for the
particular period and counting the number of roamers. Figure 19 shows the
result of such a
data sort of the data file shown in Figure 7. The number of roamers counted
for each
wireless communication network is multiplied by the corresponding roamer gross-
up
coefficient for each wireless communication network to generate an
extrapolated number of
roamers for each wireless communication network. The share of roamers for each
wireless
communication network is then generated by dividing the extrapolated number of
subscribers for each wireless communication network by the total number of
extrapolated
roamers for all wireless communication networks. Figure 20 shows the
extrapolation of the
number of roamers counted for each wireless communication network shown in
Figure 19
and the calculation of the roamer share for each wireless communication
network. A
sample report showing roamer activity over a monthly period is shown in Figure
21.
The data mining application calculates the call share for each wireless
communication network by first generating a call share gross-up factor that
accounts for
data that is missed by the data gathering nodes (120). The data mining
application sorts
through the baselining period raw data shown in Figure 6 and generates a list
counting the
number of traffic channel assignments made, which correspond to subscriber
calls. This
data sort is compared to a list of actual traffic channel assignments
generated from data
received from service providers to determine how many calls the data gathering
nodes
missed. The comparison of these two lists is shown in Figure 22. The call
share gross-up



CA 02368001 2001-09-14
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coefficient is calculated by dividing the number of actual traffic channel
assignments made
by the measured number of traffic channel assignments made.
The number of traffic channel assignments made for each wireless communication
network is multiplied by the corresponding call share gross-up coefficient for
each wireless
communication network to generate an extrapolated number of traffic channel
assignments
for each wireless communication network. The share of calls made for each
wireless
communication network is generated by dividing the extrapolated number of
traffic channel
assignments made for each wireless communication network by the total number
of
extrapolated traffic channel assignments for all wireless communication
networks. Figure
24 shows the extrapolation of the number of traffic channel assignments made
for each
wireless communication network and the calculation of call share for each
wireless
communication network. A sample report containing information on caller share
over a
monthly period is shown in Figure 25.
The data mining application also processes the data files to generate
information on
the quality of the base, new, and churning subscribers for each wireless
communication
network based upon the number of calls each subscriber of each wireless
communication
network makes. Since service provider revenues are directly tied to the number
of calls
made, information regarding quality in addition to number of subscribers is
highly
desirable. Figure 26 is a sample excerpt of a data file stored at the control
center (120) for
illustration of how the data mining application generates information on the
quality of base
subscribers for each wireless communication network. Only data for two
wireless
communication networks is shown, but a complete file will have data for all
wireless
communication network.
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The data mining application calculates the quality of base subscribers over a
particular period by sorting the data file for the particular period,
identifying each different
subscriber for each wireless communication network, and counting the number of
traffic
channel assignments made to each different subscriber. Figure 27 shows such a
data sort of
the file excerpt shown in Figure 26. This data is further sorted by number of
traffic channel
assignments to produce a list of subscribers with the highest number of
traffic channel
assignments listed first and the subscribers with the lowest number of traffic
channel
assignments listed last. Figure 28 shows such a data sort of the data found in
Figure 27. In
the presently preferred embodiment, this list is divided into quartiles based
on the number
of traffic channel assignments made. For each quartile, the number of
subscribers for each
wireless communication network is counted. Figure 29 shows such a data sort of
the data
found in Figure 28. For each quartile, the market share percentage of each
wireless
communication network is calculated by dividing the number of subscribers for
each
wireless communication network by the total number of subscribers for all
wireless
communication networks in the quartile. Figure 30 shows sample market share
calculations for base subscribers for the data found in Figure 29.
Figures 31 and 32 are sample excerpts of data files stored at the control
center (120)
for illustration of how the data mining application generates information on
the quality of
new and churning subscribers of each wireless communication network. The data
shown in
Figure 32 is taken at a particular time period later than Figure 31. The data
mining
application first identifies which subscribers are new subscribers and which
subscribers are
churning using a similar process to that described earlier when determining
the number and
share of added and churning subscribers. The data mining application
identifies the
number of new subscribers added by over a particular time period by each
wireless
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CA 02368001 2001-09-14
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communication network by comparing a list of unique subscriber identifiers of
the
particular time period to a prior time period and counting the number of
unique subscriber
identifiers that do not appear in the prior period. Similarly, the number of
subscribers for
each wireless communication network who discontinued their service at the end
of a prior
time period is approximated by comparing a list of the unique subscriber
identifiers of the
particular time period to the prior time period and counting the number of
unique
subscriber identifiers that appear in the prior time period, but not the
present time period.
Sample data excerpted from a particular time period in which it is desired to
calculate the number of new and dropped subscribers is shown in Figure 32. The
data
mining applications sorts through the raw data of Figure 32 and generates a
list of different
subscriber identifiers for each wireless communication network. The data
mining
application then sorts through the raw data of a prior time period, shown in
Figure 31, and
generates a list of different subscribers for each wireless communication
network. These
lists are compared to identify the new subscribers appearing in the particular
time period
but not the prior time period and to identify the churning subscribers
appearing in the prior
time period, but not the particular time period. The comparison of these two
lists is shown
in Figure 33.
To calculate the quality of new subscribers for each wireless communication
network, the data mining application re-sorts the data in Figure 32, counting
the number of
traffic channel assignments made to the new subscribers identified from the
data in Figure
33 for each wireless communication network. The results of this data sort are
shown in
Figure 34. This data is further sorted by number of traffic channel
assignments to produce
a list of new subscribers with the highest number of traffic channel
assignments listed first
and the new subscribers with the lowest number of traffic channel assignments
listed last.
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Figure 35 shows such a data sort of the data found in Figure 34. In the
presently preferred
embodiment, this list is divided into quartiles based on the number of traffic
channel
assignments made. For each quartile, the number of new subscribers for each
wireless
communication network is counted. Figure 36 shows such a data sort of the data
found in
Figure 35. For each quartile, the market share percentage of new subscribers
for each
wireless communication network is calculated by dividing the number of new
subscribers
for each wireless communication network by the total number of new subscribers
for all
wireless communication networks in the quartile. Figure 37 shows sample market
share
percentage calculations for new subscribers for the data found in Figure 36.
To calculate the quality of churning subscribers for each wireless
communication
network, the data mining application re-sorts the data in Figure 31, counting
the number of
traffic channel assignments made to the churning subscribers identified from
the data in
Figure 33 for each wireless communication network. The results of this data
sort are
shown in Figure 38. This data is further sorted by number of traffic channel
assignments to
produce a list of churning subscribers with the highest number of traffic
channel
assignments listed first and the new subscribers with the lowest number of
traffic channel
assignments listed last. Figure 39 shows such a data sort of the data found in
Figure 38. In
the presently preferred embodiment, this list is divided into quartiles based
on the number
of traffic channel assignments made. For each quartile, the number of churning
subscribers
for each wireless communication network is counted. Figure 40 shows such a
data sort of
the data found in Figure 39. For each quartile, the market share percentage of
churning
subscribers for each wireless communication network is calculated by dividing
the number
of churning subscribers for each wireless communication network by the total
number of
churning subscribers for all wireless communication networks in the quartile.
Figure 41
34



CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
shows sample market share percentage calculations for churning subscribers for
the data
found in Figure 40.
The data mining application calculates the peak and non-peak call share for
each
wireless communication network by first generating a peak/non-peak call share
gross-up
factor that accounts for data that is missed by the data gathering nodes
(120). This process
is the same as that performed in calculating the call share gross-up factor
shown in Figure
24 since the proportion of calls missed during peak and non-peak periods is
proportional to
the number of calls missed. The data mining application sorts through the
baselining
period raw data shown in Figure 6 and generates a list counting the number of
traffic
channel assignments made, which correspond to subscriber calls. This data sort
is
compared to a list of actual traffic channel assignments generated from data
received from
service providers to determine how many calls the data gathering nodes missed.
The
comparison of these two lists is shown in Figure 43. The peak/non-peak call
share gross-up
coefficient is calculated by dividing the number of actual traffic channel
assignments made
by the measured number of traffic channel assignments made.
The number of traffic channel assignments made during peak and non-peak hours
for each wireless communication network is multiplied by the corresponding
peak/non-
peak call share gross-up coefficient for each wireless communication network
to generate
an extrapolated number of traffic channel assignments during peak and non-peak
hours for
each wireless communication network. The share of calls made during peak and
non-peak
hours for each wireless communication network is generated by dividing the
extrapolated
number of peak and non-peak traffic channel assignments made for each wireless
communication network by the total number of extrapolated peak and non-peak
traffic
channel assignments for all wireless communication networks. Figure 42 is a
sample



CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
excerpt of a data file from which peak and non-peak call information is to be
generated.
Figure 44 shows the data sort of Figure 42 counting the number of peak and non-
peak
traffic channel assignments made for each wireless communication network. Peak
hours
are defined to be between the hours of 07:00 and 19:00 whereas non-peak hours
are defined
to be between the hours of 19:00 and 07:00. Figure 45 shows the extrapolation
of the
number of traffic channel assignments made during peak and non-peak hours for
each
wireless communication network and the calculation of peak and non-peak call
share for
each wireless communication network. Also shown in Figure 45 is the
calculation of peak
and non-peak call share for each wireless communication network excluding all
roamer
calls.
The data mining application calculates the incoming and outgoing call share
for
each wireless communication network by first generating an incoming/outgoing
call share
gross-up coefficient that accounts for data that is missed by the data
gathering nodes (120).
This incoming/outgoing call share gross-up coefficient is equal to the value
of the call share
and peak/non-peak call share gross-up coefficient.
Figure 46 is a sample excerpt of a data file from which incoming and outgoing
call
share information is to be generated. The data mining application sorts the
data file shown
in Figure 46 and identifies the traffic channel assignments and pages for each
wireless
communication network. To identify which traffic channel assignments are
incoming calls
and which are outgoing calls, the data mining application sorts the file shown
in Figure 47.,
identifying which traffic channel assignments are immediately preceded within
2 to 4
seconds by a page to the same subscriber. These traffic channel assignments
are classified
as incoming calls, and all other traffic channel assignments are classified as
outgoing. Any
traffic channel assignments during the first three seconds of the file data
gathering period
36



CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
are not considered because it is unknown whether there was a corresponding
page to these
traffic channel assignments. The results of this data sort identifying
incoming and outgoing
calls are shown in Figure 48.
The number of incoming and outgoing call traffic channel assignments made
during
peak and non-peak hours for each wireless communication network is multiplied
by the
corresponding incoming/outgoing call share gross-up coefficient for each
wireless
communication network to generate an extrapolated number of incoming and
outgoing call
traffic channel assignments for each wireless communication network. The share
of
incoming and outgoing calls for each wireless communication network is
generated by
dividing the extrapolated number of incoming and outgoing calls for each
wireless
communication network by the total number of incoming and outgoing calls for
all wireless
communication networks. Figure 49 shows the extrapolation of the number of
incoming
and outgoing call traffic channel assignments for each wireless communication
network
and the calculation of incoming and outgoing call share for each wireless
communication
network. Also shown in Figure 49 is the calculation of incoming and outgoing
call share
for each wireless communication network excluding all roamer calls.
In markets where a service provider operates both an analog wireless
communication network and a digital wireless communication network, dual mode
cell
phones are often issued to subscribers which can operate on either the analog
or digital.
networks. When either an incoming call is received or outgoing call is made,
the forward
control channel either assigns a digital or analog traffic channel, depending
on network
capacity at the time of the call. Dual mode users can be identified from the
gathered data
since traffic channel assignments for the same subscriber will be present in
both the analog
and digital wireless communication networks for a service provider. The data
mining
37



CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
application can determine the share of analog and digital traffic channel
assignments made
to a subscriber by counting the number of analog and digital traffic channel
assignments
made and dividing each by the total number of traffic channel assignments
made.
The data gathered and the market share and usage characterization information
generated by the data mining application of the present invention has many
practical
applications for wireless communication network service providers. The
information
allows service providers to ( 1 ) tailor their sales and marketing
expenditures toward this
customer base, (2) evaluate the success of pricing, promotions, and
advertising programs
introduced within a market, (3) quantitatively compare themselves to
competitors, and (4)
better understand the utilization patterns of the customer base within a
region, such as at
new cell site locations. On a regional or national level, comparisons can be
made between
competing service providers on a broader geographic basis encompassing several
cities, or
to track usage in new PCS markets or high subscriber growth cities. The area
code and first
three digits of subscriber MINS can be correlated to zip codes, thus allowing
the number of
existing, churning, and new subscribers in each zip code of a region for each
service
provider to be determined. This allows each service provider to identify areas
in which
they are weak and where additional sales and marketing efforts are required.
Population
demographics based on zip codes can be used to characterize and understand the
demographics of the subscribers for each service provider, thus enabling
service providers
to design their sales and marketing efforts with particular demographic groups
in mind.
If the public key of the private/public key pair used to encrypt the
subscriber MINs
is provided to a service provider along with the unique subscriber identifiers
for its own
customers, the service provider can decrypt the unique subscriber identifiers
into subscriber
MINS. The data gathered by the present invention on a particular service
provider can then
38



CA 02368001 2001-09-14
WO 00/56098 PCT/US00/06652
be utilized by that service provider in a variety of ways. A service provider
can compare
the gathered data to their internal records to verify proper billing and
identify and track
fraud. The present invention can also be used by service providers in
conducting
functionality tests of their systems, such as whether pages are being properly
sent by a
network. The data gathered from the present information can also be used by
service
providers to track individual subscriber usage patterns, such as time, day,
and location of
calls. Individual subscriber usage can also be tracked over a period of time
to provide a
profile and identify trends in usage. For example, usage can be tracked by
season to
identify seasonal trends, or drastic changes in usage by a subscriber can be
identified.
Tracking individual subscriber usage patterns allows service providers to
identify or
generate pricing plans most appropriate for an individual subscriber, thereby
enhancing
subscriber satisfaction and retention.
While the present invention has been particularly described with respect to
the
illustrated embodiments, it will be appreciated that various alterations,
modifications and
adaptations may be made based on the present disclosure, and are intended to
be within the
scope of the present invention. While the invention has been described in
connection with
what are presently considered to be the most practical and preferred
embodiments, it is to
be understood that the present invention is not limited to the disclosed
embodiment but, on
the contrary, is intended to cover various modifications and equivalent
arrangements
included within the scope of the appended claims.
39

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Administrative Status

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Administrative Status

Title Date
Forecasted Issue Date Unavailable
(86) PCT Filing Date 2000-03-14
(87) PCT Publication Date 2000-09-21
(85) National Entry 2001-09-14
Examination Requested 2003-05-21
Dead Application 2006-03-14

Abandonment History

Abandonment Date Reason Reinstatement Date
2002-03-14 FAILURE TO PAY APPLICATION MAINTENANCE FEE 2002-07-03
2003-03-14 FAILURE TO PAY APPLICATION MAINTENANCE FEE 2003-06-19
2004-03-15 FAILURE TO PAY APPLICATION MAINTENANCE FEE 2004-05-04
2005-03-14 FAILURE TO PAY APPLICATION MAINTENANCE FEE

Payment History

Fee Type Anniversary Year Due Date Amount Paid Paid Date
Application Fee $300.00 2001-09-14
Registration of a document - section 124 $100.00 2002-01-24
Registration of a document - section 124 $100.00 2002-01-24
Reinstatement: Failure to Pay Application Maintenance Fees $200.00 2002-07-03
Maintenance Fee - Application - New Act 2 2002-03-14 $100.00 2002-07-03
Request for Examination $400.00 2003-05-21
Reinstatement: Failure to Pay Application Maintenance Fees $200.00 2003-06-19
Maintenance Fee - Application - New Act 3 2003-03-14 $100.00 2003-06-19
Reinstatement: Failure to Pay Application Maintenance Fees $200.00 2004-05-04
Maintenance Fee - Application - New Act 4 2004-03-15 $100.00 2004-05-04
Owners on Record

Note: Records showing the ownership history in alphabetical order.

Current Owners on Record
TELEPHIA, INC.
Past Owners on Record
FRANGIONE, TOM
HEIDOHRN, MARK
OYLER, JOHN
PEYRAT, ALAN
Past Owners that do not appear in the "Owners on Record" listing will appear in other documentation within the application.
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Document
Description 
Date
(yyyy-mm-dd) 
Number of pages   Size of Image (KB) 
Drawings 2001-09-14 49 1,762
Description 2001-09-14 39 1,748
Abstract 2001-09-14 1 53
Claims 2001-09-14 22 929
Cover Page 2002-03-12 1 34
PCT 2001-09-14 12 520
Assignment 2001-09-14 3 91
Correspondence 2002-03-08 1 25
Assignment 2002-01-24 11 465
Prosecution-Amendment 2003-05-21 1 25
Prosecution-Amendment 2003-07-08 1 37
PCT 2001-09-15 7 323