Wireless communications systems and methods for short-code multiple user detection

• US 7,248,623 B2
• Filed: 03/14/2002
• Issued: 07/24/2007
• Est. Priority Date: 03/14/2001
• Status: Active Grant

• Current Assignee: Mercury Systems, Incorporated
• Original Assignee: Mercury Computer Systems Incorporated
• Inventors: Oates, John H.
• Primary Examiner(s): Ghebretinsae; Temesghen
• Assistant Examiner(s): Torres; Juan Alberto
• Application Number:
  US10/099,536
• Publication Number:
  US 20030099224A1
• Time in Patent Office: 1,958 Days
• Field of Search: 375/148, 375/150, 375/144
• US Class Current: 375/148
• 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 short code spread spectrum waveforms transmitted by one or more users of a spread spectrum system, comprising

generating a matrix indicative of cross correlations among the waveforms as a composition of a first component that represents correlations among time lags and short codes 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,

generating, as a function of the correlation matrix, detection statistics corresponding to symbols generated by the users and encoded in the waveforms, and generating estimates of the symbols based on the detection statistics,

wherein the first component is updated on a time scale commensurate with a rate of change of the time lags associated with the waveforms transmitted by the users and the second component is updated on a time scale commensurate with a rate of change of the multipath amplitudes associated with waveforms transmitted by the users.

2. The method of claim 1, wherein the spread spectrum waveforms are channel corrupted.

3. The method of claim 1, wherein the step of updating the second component is executed on a shorter time scale than that of updating the first component.

4. The method of claim 1, further comprising generating the first component of the cross correlation matrix as a composition of

(i) a first matrix component indicative of correlations among short codes associated with the respective users and

(ii) a second matrix component indicative of the waveforms transmitted by the users and the time lags associated therewith.

5. The method of claim 4, further comprising updating the first matrix component upon addition or removal of a user to the spread spectrum system.

6. The method of claim 4, further comprising computing the first matrix component as a convolution of the short code associated with each user with the short codes of other users.

7. The method of claim 1, further comprising the step of selecting each user to be composed of a plurality of virtual users, wherein each virtual user transmits one bit in a symbol period.

8. A method of processing short code spread spectrum waveforms transmitted by one or more users of a spread spectrum system, comprising

generating a matrix indicative of cross correlations among the waveforms as a composition of a first component that represents correlations among time lags and short codes 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,

generating estimates of symbols transmitted by the users and encoded in said waveforms as a function of the cross-correlation matrix,

wherein the correlations among the short codes associated with the waveforms transmitted by the users are defined in accord with by the relation:

${\mathrm{\Gamma <br><br>}}_{\mathrm{ik}}<br><br>\left[m\right]\equiv <br><br>\frac{1}{2<br><br>N_l}<br><br>\underset{n=0}{\overset{N-1}{\sum <br><br>}}<br><br>c_l^{*}·<br><br>c_k<br><br>\left[n-m\right]$

wherein

Γ

_lk[m] represents correlation between l and k users corresponding to m^th transmitted symbol,

c_l*[n] represents complex conjugate of the short code sequence associated with the l^th user,

c_k [n−

m] represents the short code sequence associated with k^th user,

m is a symbol period,

N represents the length of the code, and

N_l represent the number of non-zero length of the code,

wherein the first component is updated on a time scale commensurate with a rate of change of the time lags associated with the waveforms transmitted by the users and the second component is updated on a time scale commensurate with a rate of change of the multipath amplitudes associated with waveforms transmitted by the users.

9. The method of claim 8, wherein the step of estimating the symbols further comprises generating, as a function of the correlation matrix, detection statistics corresponding to symbols generated by the users and encoded in the waveforms.

10. The method of claim 9, wherein the step of estimating the symbols comprises utilizing the detection statistics to estimate the symbols.

11. A method of processing short code spread spectrum waveforms transmitted by one or more users of a spread spectrum system, comprising

generating a matrix indicative of cross correlations among the waveforms as a composition of a first component that represents correlations among time lags and short codes 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,

generating estimates of symbols transmitted by the users and encoded in said waveforms as a function of the cross-correlation matrix,

wherein the correlations among the short codes associated with the waveforms transmitted by the users are defined in accord with by the relation:

${\mathrm{\Gamma <br><br>}}_{\mathrm{ik}}<br><br>\left[m\right]\equiv <br><br>\frac{1}{2<br><br>N_l}<br><br>\underset{n=0}{\overset{N-1}{\sum <br><br>}}<br><br>c_l^{*}·<br><br>c_k<br><br>\left[n-m\right]$

wherein

Γ

_lk[m] represents correlation between l and k users corresponding to m^th transmitted symbol,

c_l*[n] represents complex conjugate of the short code sequence associated with the l^th user,

c_k[n−

m] represents the short code sequence associated with k^th user,

m is a symbol period,

N represents the length of the code, and

N_l represent the number of non-zero length of the code,

wherein the step of estimating the symbols further comprises generating, as a function of the correlation matrix, detection statistics corresponding to symbols generated by the users and encoded in the waveforms, and

wherein the step of estimating the symbols comprises utilizing the detection statistics to estimate the symbols

wherein the first component of the cross-correlation matrix is defined in accord with the relation;

$C_{\mathrm{lkqq}}·<br><br>\left[m\right]=\underset{m}{\sum <br><br>}<br><br>g<br><br>\left[{\mathrm{mN}}_c+\mathrm{\tau <br><br>}\right]·<br><br>{\mathrm{\Gamma <br><br>}}_{\mathrm{lk}}<br><br>\left[m\right]$

wherein

g is a pulse shape vector,

N_c is the number of samples per chip,

τ

is a time lag, and

Γ

represents the Γ

matrix defined above.

12. The method of claim 11, wherein the cross-correlation matrix is defined in accord with the relation:

$r_{\mathrm{lk}}<br><br>\left[m\right]=\underset{q=1}{\overset{L}{\sum <br><br>}}<br><br>\underset{q^{\mathrm{\prime <br><br>}}=1}{\overset{L}{\sum <br><br>}}<br><br>\mathrm{Re}<br><br>\left\{{\hat{a}}_{\mathrm{lq}}^{*}<br><br>a_{{\mathrm{kq}}^{\mathrm{\prime <br><br>}}}·<br><br>C_{{\mathrm{lkqq}}^{\mathrm{\prime <br><br>}}}<br><br>\left[m\right]\right\}=\mathrm{Re}<br><br>\left\{a_l^H·<br><br>C_{\mathrm{lk}}<br><br>\left[m\right]·<br><br>a_k\right\}$

wherein

m is a symbol period,

Re denotes the real part of a complex expression,

a_k is a columnar matrix representing multipath amplitude components associated with the k^th user,

â

_lq* is an estimate of a_lq* which is the complex conjugate of one multipath amplitude component of the l^th user,

a_kq′

is one multipath amplitude component associated with the k^th user, and

C denotes the C matrix defined above.

13. The method of claim 12, wherein the detection statistics are obtained in accord with the following relation:

$\begin{array}{c}{y}_l<br><br>\left[m\right]=<br><br>r_{\mathrm{ll}}<br><br>\left[0\right]<br><br>b_l<br><br>\left[m\right]+\underset{k=1}{\overset{K_v}{\sum <br><br>}}<br><br>r_{\mathrm{lk}}<br><br>\left[-1\right]<br><br>b_k<br><br>\left[m+1\right]+\\ <br><br>\underset{k=1}{\overset{K_v}{\sum <br><br>}}<br><br>\left[r_{\mathrm{lk}}<br><br>\left[0\right]-r_{\mathrm{ll}}<br><br>\left[0\right]<br><br>{\mathrm{\delta <br><br>}}_{\mathrm{lk}}\right]<br><br>b_k<br><br>\left[m\right]+\underset{k=1}{\overset{K_v}{\sum <br><br>}}<br><br>r_{\mathrm{lk}}<br><br>\left[1\right]<br><br>b_k<br><br>\left[m-1\right]+{\mathrm{\eta <br><br>}}_l<br><br>\left[m\right]\end{array}$

wherein

y_l[m] represents detection statistics for mth symbol transmitted by the l^th user,

r_ll[0]b_l[m] represents a signal of interest, and

remaining terms of the relation represent Multiple Access Interference (MAI) and noise.

14. The method of claim 13, wherein the step of generating estimates comprises performing multi-stage decision-feedback interference cancellation (MDFIC).

15. The method of claim 14, wherein the step of performing MDFJC includes estimating symbols in accord with the relation:

$\begin{array}{c}{\hat{b}}_l<br><br>\left[m\right]=<br><br>\mathrm{sign}<br><br>\{y_l<br><br>\left[m\right]-\underset{k=1}{\overset{K_v}{\sum <br><br>}}<br><br>r_{\mathrm{lk}}<br><br>\left[-1\right]<br><br>{\hat{b}}_k<br><br>\left[m+1\right]-\underset{k=1}{\overset{K_v}{\sum <br><br>}}<br><br>[r_{\mathrm{lk}}<br><br>\left[0\right]-\\ <br><br>r_{\mathrm{ll}}<br><br>\left[0\right]<br><br>{\mathrm{\delta <br><br>}}_{\mathrm{lk}}]<br><br>{\hat{b}}_k<br><br>\left[m\right]-\underset{k=1}{\overset{K_v}{\sum <br><br>}}<br><br>r_{\mathrm{lk}}<br><br>\left[1\right]<br><br>{\hat{b}}_k<br><br>\left[m-1\right]\}\end{array}$

wherein

{circumflex over (b)}_l[m] represents an estimate of the m^th symbol transmitted by the l^th user.

16. The method of claim 15, further comprising the step of updating the C-matrix upon occurrence of a change in a user'"'"'s delay lag time.

17. A method of processing short code spread spectrum waveforms transmitted by one or more users of a spread spectrum system, comprising

generating a matrix indicative of cross correlations among the waveforms as a composition of a first component that represents correlations among time lags and short codes 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,

generating estimates of symbols transmitted by the users and encoded in said waveforms

wherein the first component is updated on a time scale commensurate with a rate of change of the time lags associated with the waveforms transmitted by the users and the second component is updated on a time scale commensurate with a rate of change of the multipath amplitudes associated with waveforms transmitted by the users.

18. The method of claim 17, wherein the step of generating estimates of the symbols further comprises generating, as a function of the correlation matrix, detection statistics corresponding to the symbols.

19. The method of claim 18, further comprising the step of updating the first component of the correlation matrix on a first time scale and updating the second component of the correlation matrix on a second time scale, wherein the second time scale is shorter than the first time scale.