Multi-user detection for antenna array receivers

Details Multi-user detection for antenna array receivers Multi-user detection for antenna array receivers

1998-12-02

2003-05-13

Vuong, Quochien (Department: 2681)

Telecommunications

Transmitter and receiver at separate stations

Distortion, noise, or other interference prevention,...

C455S562100, C342S354000, C370S342000

Reexamination Certificate

active

06564037

ABSTRACT:

FIELD OF THE INVENTION
The present invention relates to radio cellular mobile communications and in particular relates to multi-user detection for code division multiple access antenna array receivers.
BACKGROUND OF THE INVENTION
To cope with the increasing demand for cellular mobile communications it is necessary to find ways to increase system capacity on the reverse link whilst avoiding system complexity.
The cellular mobile communications IS-95 standard describes the use of direct sequence code division multiple access (CDMA) techniques. In such systems, each user is allocated a distinct pseudo-noise (PN) code. The signal from each user is multiplied by a respective code before transmission to the base station. All users transmit using the same radio frequency carrier. The signals from different users will arrive asynchronously due to their different locations and signals from each user may arrive asynchronously due to multipath propagation.
FIG. 1
is an algebraic representation of a CDMA communications link. The vector d contains N consecutive binary data symbols for P users. When these symbols are transmitted, they are subject to multipath distortion. This causes the receiver to observe J versions of each transmitted symbol, which arrive at different times. This effect is defined mathematically by two matrices. Multiplying d by the matrix T repeats each symbol J times. The size NPJ matrix A is diagonal. Its diagonal elements are the positive square roots of the received multipath fading powers for the NP signals received on J paths. This results in the received signal being characterised as the product ATd. The size NPJ×NPJ matrix (R/L)D represents the combined effects of beamforming and of pseudo-noise coding and decoding, where L is the CDMA processing gain. The size NPJ×NPJ matrix R is Hermitian [Horn92, p169] (R. A. Horn and C. R. Johnson, “Matrix Analysis”, Cambridge University Press, Cambridge (UK), 1992.) The size NPJ×NPJ matrix D is diagonal [Horn92, p23]. The quantity y=(R/L)DATd+z/L represents the processed received signal plus background noise (the size NPJ vector z/L).
The vector y may be subject to conventional bit detection techniques, e.g. as described in [Proakis95] (J. G. Proakis, “Digital Communications (3rd Ed)”, McGraw-Hill, 1995). Alternatively, the capacity of such a system may be improved by employing multi-user detection (MUD) techniques in which information about multiple users is used to detect a desired user. Another way of increasing the capacity of the system is by employing a steerable beam antenna array at the base station. This enables the multiple access interference (MAI) between users transmitting from distinctly different bearings to be reduced. However, the MAI between users transmitting from a similar bearing may not be reduced.
It is known that by using multi-user detection [Moshavi 96] (S. Moshavi, “Multi-user Detection for DS-CBMA Communications”, IEEE Personal Comms Mag, Vol 34(10), October 1996, pp124-35) or antenna array receivers [Naguib94] (A. F. Naguib, A. Paulraj and T. Kailath, “Capacity Improvement with Base Station Antenna Arrays in Cellular CDMA”, IEEE Trans Veh Tech, Vol 43(3), August 1994, pp 691-7), bit error rates considerably lower than those provided by the conventional detector can be achieved for the reverse link of a cellular direct sequence code division multiple access system. Results displayed in
FIGS. 8
a, b
-
16
a, b
confirm these findings for both Additive White Gaussian Noise (AWGN) channels and Rayleigh fading single and multipath channels. Initial beamforming followed by multi-user detection can further decrease bit error rate for these channels (see
FIGS. 8
b
-
16
b
), and hence increase capacity, but at a cost in complexity.
FIG. 3
shows a generic receiver employing beamforming followed by multi-user detection. The system is necessarily complicated and computational requirements are high.
Several detection systems exist to provide an estimate of a vector of transmitted bits d, given an output y. The detectors under consideration are the conventional (single user) detector and four multi-user detectors, namely the linear decorrelator detector, the linear minimum mean square error (MMSE) detector, the non-linear decision feedback decorrelator and a form of subtractive interference cancellation (also non-linear). The latter four are usually described for the case of single path transmission (J=1 and T=I, where I is the identity matrix [Horn92, p6]) and in the absence of fading (D=I), that is, when y=(R/L)Ad+z/L.
In the simplest system, single-user detection is employed. The signal from a particular user is detected by correlating the received signal, which is a sum of signals from all transmitting users, with the PN code of the user. The matched filter detector estimates the transmitted bits according to the signs of the real parts of the received output y. The signals from other users interfere with the desired signal and the system capacity is limited by multiple access interference.
The linear decorrelator detector employs an inversion of an estimate of the matrix R/L in order to estimate Ad, where L is the processing gain. A positive definite Hermitian estimate of R, say R′, is calculated using knowledge of the PN codes, delays, phases and array signatures of the P users. Then R′/L is inverted using the Cholesky decomposition [Horn92, p407] and the transmitted bits are estimated according to the signs of the real parts of the components of (R′/L)
−1
y. Estimates of the received signal powers are not required.
The MMSE detector is represented by an NP×NP matrix C which minimises the following expression:
∑
k
=
0
NP
-
1
⁢
ϵ
⁡
[
&LeftDoubleBracketingBar;
(
C
⁢
y
_
-
A
⁢
d
_
)
k
&RightDoubleBracketingBar;
2
]
.
A closed form expression for C can be determined following a method suggested by [Honig95] (M. Honig, U. Madhow and S. Verdu, “Blind Adaptive Multiuser Detection”, IEEE Trans. Info. Theory, Vol. 41(4), July 1995, pp
954-960). The result for C is obtained as:
C
MMSE
=((
R/L
)+(&sgr;
2
/L
i
)
A
−2
)
−1
where &sgr;
2
denotes the background noise variance and A
−1
denotes the matrix inverse operation [Horn92, p14]. The MMSE detector takes into account both the background noise and the received signal powers. In general, the MMSE detector does not enhance the noise as much as the decorrelator and so provides a better bit error rate. Estimates of the received signal powers and the level of background noise are required.
The decision feedback decorrelator makes bit decisions in the order of decreasing received signal powers. Hence these powers need to be estimated. It employs a Cholesky decomposition to factor the positive definite Hermitian matrix R into F
H
F, where F is a lower triangular matrix and F
H
is the Hermitian adjoint or transpose [Horn92, p6] of F. The filter {square root over (L)}(F
H
)
−1
is applied to the sampled output y to yield:
{square root over (L)}
(
F
H
)
−1
y
=(
F/{square root over (L)}
)
Ad+{square root over (L)}
(F
H
)
−1
z/L
In practice, R can be estimated and hence F. As F/{square root over (L)} is lower triangular, the k-th component of {square root over (L)}(F
H
)
−1
y does not contain a multiple access interference term for any other bit k′>k. So the 0-th component does not contain an MAI term due to any other bit. A decision for this bit is determined by the sign of the real part of the component. For k>0, we use feedback in the sense that the hard decisions for all bits k″<k are used to subtract the MAI from the k-th component of the output. The received signal amplitudes are required for this. Finally, a hard decision for the k-th bit is made.
Subtractive interference cancellation estimates the transmitted bits in order of decreasing received signal powers

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