Bayesian-update based location prediction method for CDMA systems

• US 6,564,065 B1
• Filed: 04/20/1999
• Issued: 05/13/2003
• Est. Priority Date: 04/20/1999
• Status: Expired due to Term

• Current Assignee: Nokia of America Corporation (Nokia Corporation)
• Original Assignee: Lucent Technologies, Inc. (Nokia Corporation)
• Inventors: Chen, Byron H., Rege, Kiran M., Jeske, Daniel R., Chang, Kirk K., Freidenfelds, John, Chiang, Tung C.
• Primary Examiner(s): Hunter, Daniel
• Assistant Examiner(s): Tran, Pablo N
• Application Number:
  US09/294,997
• Time in Patent Office: 1,484 Days
• Field of Search: 455/456, 455/436, 455/440, 455/524, 455/450, 455/426, 455/422, 455/457, 342/357.1, 342/357.2, 342/357.3, 342/357.4, 370/528
• US Class Current: 455/457
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

The location of a mobile unit in the service area of a CDMA cellular telephone system is predicted from a spatial probability distribution that is generated over a region of sub-cells within the service area. The spatial distribution, and hence the predicted location, is updated sequentially based on RF measurements provided by the mobile unit through the use of a Bayesian-update method.

Claims

1. A method of estimating the location of a mobile communications unit in a communications service area, comprising the steps of:

(a) detecting attribute information at the mobile unit, said attribute information being specific to the location wherein the mobile unit is presently located;

(b) transmitting the attribute information to a remote location;

(c) computing a probability distribution of the mobile unit being at different locations within the service area using a first and a second set of probability values related to mobile unit location, the first set of probability values including pilot signal visibility probabilities, and the second set of probability values including phase-offset probabilities; and

(d) generating an output indicative of the location probability distribution, the detected attribute information including pilot signal power received from a base station located in the service area and phase-offset of a pilot signal observed by the mobile unit relative to a predetermined pilot signal.

2. A method according to claim 1 wherein said step (b) of computing uses a Bayes theorem.

3. A method according to claim 2 wherein the location probability distribution computed in step (b) comprises an a-posteriori location probability distribution.

4. A method according to claim 3 wherein the location probability distribution is iteratively updated at predetermined time intervals.

5. A method according to claim 3 and additionally including a step (d) prior to step (b) of sub-dividing the service area into a plurality of sub-areas and using at least one of said sub-areas in step (b) so as to reduce the number of computations required therein.

6. A method according to claim 1 and additionally including the steps of:

(d) generating an RF a propagation model of the service area; and

(e) generating and storing a database containing said pilot visibility probabilities for a predetermined number of locations within a service area using the RF signal propagation model.

7. A according to claim 6 and additionally including a step (f) of generating said phase offset probabilities by a statistical model of conditional probability of the mobile unit observing a specific pilot signal phase-offset at said predetermined number of locations within the service area.

8. A method according to claim 7 wherein said phase offset probabilities are generated on demand in real time.

9. A method according to claim 6 wherein the step (d) includes making parameter measurements along a selected number of representative routes in the service area for tuning the RF propagation model to the measured parameters.

10. A method according to claim 9 wherein the service area is defined by a plurality of cells which are further divided into a plurality of sub-cells.

11. A method according to claim 9 wherein the step (e) of generating the database includes running a simulation based on the RF propagation model for a predetermined number of the sub-cells in the service area.

12. A method according to claim 11 wherein said step of running a simulation comprises running a simulation for all of the sub-cells in the service area.

13. A method according to claim 6 wherein the RF propagation model includes a plurality of parameters having values which are determined, in accordance with the specific environment of the service area.

14. A system for estimating the location of a mobile communications unit in a communication service area comprising:

a plurality of base stations located in the service area, each of said base stations including a sectorized antenna for a plurality of mutually adjacent communication signal sectors each generating a respective pilot signal having a different carrier frequency;

computing apparatus for calculating, through the use of a statistical model, the probability of the mobile unit observing a set of phase-offsets of one or more of the pilot signals given its location;

a memory for storing a database containing pilot signal visibility probabilities for a predetermined number of locations in the service area,

said computing apparatus additionally calculating a location probability distribution of the mobile unit being at a plurality of different locations in the service area in response to the pilot signal visibility probabilities and the phase-offset conditional probabilities.

15. The system according to claim 14 wherein said computing apparatus comprises a digital server, and wherein said server apparatus and said memory are connected to the mobile switching center.

16. The system according to claim 14 wherein the location probability distribution is calculated using a Bayes theorem.

17. A system according to claim 16 wherein the location probability distribution comprises an a posteriori location probability distribution.

18. A system according to claim 17 wherein the location probability distribution is iteratively updated at predetermined time intervals.

19. A system according to claim 14 wherein the service area is subdivided into a plurality of sub-areas including at least one base station therein.