Load balancing computational methods in a short-code spread-spectrum communications system

• US 20030091106A1
• Filed: 03/14/2002
• Published: 05/15/2003
• Est. Priority Date: 03/14/2001
• Status: Active Grant

• Current Assignee: Mercury Systems, Incorporated
• Original Assignee: Mercury Computer Systems Incorporated
• Inventors: Oates, John H.
• Granted Patent: US 7,203,221 B2
• Time in Patent Office: Days
• US Class Current: 375/150
• CPC Class Codes: H04B 1/707 using direct sequence modulation
• CPC Class Codes: H04B 1/7093 Matched filter type
• CPC Class Codes: H04B 1/7105 Joint detection techniques, e.g. linear detectors
• CPC Class Codes: H04B 1/71052 using decorrelation matrix
• CPC Class Codes: H04B 1/71075 Parallel interference cancellation
• CPC Class Codes: H04B 1/7115 Constructive combining of multi-path signals, i.e. RAKE receivers
• CPC Class Codes: H04B 2201/70707 Efficiency-related aspects
• CPC Class Codes: H04B 2201/70711 with modular structure

Abstract

The invention provides methods and apparatus for multiple user detection (MUD) processing that have application, for example, in improving the capacity CDMA and other wireless base stations. One aspect of the invention provides a multiprocessor, multiuser detection system for detecting user transmitted symbols in CDMA short-code spectrum waveforms. A first processing element generates a matrix (hereinafter, “gamma matrix”) that represents a correlation between a short-code associated with one user and those associated with one or more other users. A set of second processing elements generates, e.g., from the gamma matrix, a matrix (hereinafter, “R-matrix”) that represents cross-correlations among user waveforms based on their amplitudes and time lags. A third processing element produces estimates of the user transmitted symbols as a function of the R-matrix.

Claims

1. A method of processing spread spectrum waveforms transmitted by a plurality of users of a spread spectrum system, comprising

distributing among a plurality of logic units parallel tasks each for computing a portion of a matrix indicative of cross correlations among the waveforms transmitted by the users,

executing with the plurality of logic units the distributed tasks.

2. The method of claim 1, wherein the step of distributing comprises partitioning computation of the cross-correlation matrix such that a computational load associated with a task distributed to one of said logic units is substantially equal to computational load associated with another task distributed to another logic unit.

3. The method of claim 2, further comprising generating detection statistics corresponding to symbols transmitted by the users and encoded in the waveforms as a function of the cross correlation matrix.

4. The method of claim 3, further comprising generating estimates of the symbols based on the detection statistics.

5. The method of claim 3, further comprising the step of defining a metric associated with each partition in accord with the relation:

6. The method of claim 5, further comprising the step of representing the cross-correlation matrix as a composition of a rectangular component and a triangular component.

7. The method of claim 6, wherein each area A includes a first portion corresponding to the rectangular component and a second portion corresponding to the triangular component of the cross-correlation matrix.

8. The method of claim 7, wherein the step of partitioning the matrix includes selecting the matrix associated with the partitions to be substantially equal.

9. The method of claim 6, wherein the cross-correlation matrix is computed as a composition of a first component that represents correlations among time lags and code sequences associated with the waveforms transmitted by the users and a second component that represents correlations among multipath signal amplitudes associated with the waveforms transmitted by the users.

10. A method of processing spread spectrum waveforms transmitted by a plurality of users of a spread spectrum system, comprising

partitioning computation of a matrix representing cross-correlations among the waveforms transmitted by the users in accord with a pre-defined metric,

distributing among a plurality of logic units parallel tasks each corresponding to one of said partitions for computing a portion of the matrix, and

executing with the plurality of logic units the distributed tasks.

11. The method of claim 10, further comprising assembling said computed portions to generate the cross-correlation matrix.

12. The method of claim 11, wherein the step of partitioning comprises defining the metric in accord with the relation:

13. The method of claim 12, further comprising the step of generating detection statistics corresponding to symbols transmitted by the users and encoded in said waveforms as a function of the cross-correlation matrix.

14. The method of claim 13, further comprising estimating the symbols based on said detection statistics.

15. The method of claim 14, further comprising representing the cross-correlation matrix as a composition of a first component that represents correlations among time lags and code sequences associated with the waveforms transmitted by the users and a second component that represents correlations among multipath signal amplitudes associated with the waveforms transmitted by the users.

16. The method of claim 15, further comprising the step of computing correlations among the code sequences associated with the respective users in accord with the relation:

17. The method of claim 16, further comprising the step of computing the first component of the cross correlation matrix as a matrix component (herein referred to as C matrix) in accord with the relation:

18. The method of claim 17, further comprising the step of computing the cross-correlation matrix (herein referred to as r matrix) in accord with the relation:

19. The method of claim 18, wherein the step of generating detection statistics comprises computing the detection statistics in accord with the relation:

20. The method of claim 19, wherein the step of generating symbol estimates comprises computing the estimates in accord with the relation: