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Adaptive blind signal and image processing

Space-time processing can improve network capacity, coverage, and quality by reducing co-channel interference (CCI) while enhancing diversity and array gain. This article focuses largely on the receive (mobile-to-base station) time-division multiple access (TDMA) (nonspread modulation) application for high-mobility networks. We describe a large (macro) cell propagation channel and discuss different physical effects such as path loss, fading delay spread, angle spread, and Doppler spread. We also develop a signal model incorporating channel effects. Both forward-link (transmit) and reverse-link (receive) channels are considered and the relationship between the two is discussed. Single- and multiuser models are treated for four important space-time processing problems, and the underlying spatial and temporal structure are discussed as are different algorithmic approaches to reverse link space-time professing with blind and nonblind methods for single- and multiple-user cases. We cover forward-link space-time algorithms and we outline methods for estimation of multipath parameters. We also discuss applications of space-time processing to CDMA, applications of space-time techniques to current cellular systems, and industry trends.

Space-time processing for wireless communications

Direct sequence (DS) code division multiple access (CDMA) is a promising technology for wireless environments with multiple simultaneous transmissions because of several features: asynchronous multiple access, robustness to frequency selective fading, and multipath combining. The capacity of DS-CDMA systems is interference-limited and can therefore be increased by techniques that suppress interference. In this paper, we present developments in interference suppression using blind adaptive receivers that do not receive knowledge of the signal waveforms and propagation channels of the interference, and that require a minimal amount of information about the desired signal. The framework considered generalizes naturally to include additional capabilities such as receive antenna diversity. The most powerful application of the methods described here is for linearly modulated CDMA systems with short spreading waveforms (i.e., spreading waveforms with period equal to the symbol interval), for which they provide substantial performance gains over conventional reception. Implications for future system design due to the restriction of short spreading waveforms and directions for further investigation are discussed.

Blind adaptive interference suppression for direct-sequence CDMA

Multiuser demodulation algorithms for centralized receivers of asynchronous direct-sequence (DS) spread-spectrum code-division multiple-access (CDMA) systems in frequency-selective fading channels are studied. Both DS-CDMA systems with short (one symbol interval) and long (several symbol intervals) spreading sequences are considered. Linear multiuser receivers process ideally the complete received data block. The approximation of ideal infinite memory-length (IIR) linear multiuser detectors by finite memory-length (FIR) detectors is studied. It is shown that the FIR detectors can be made near-far resistant under a given ratio between maximum and minimum received power of users by selecting an appropriate memory-length. Numerical examples demonstrate the fact that moderate memory-lengths of the FIR detectors are sufficient to achieve the performance of the ideal IIR detectors even under severe near-far conditions. Multiuser demodulation in relatively fast fading channels is analyzed. The optimal maximum likelihood sequence detection receiver and suboptimal receivers are considered. The parallel interference cancellation (PIC) receiver is demonstrated to achieve better performance in known channels than the decorrelating receiver, but it is observed to be more sensitive to channel coefficient estimation errors than the decorrelator. At high channel loads the PIC receiver suffers from bit error rate (BER) saturation, whereas the decorrelating receiver does not. Choice of channel estimation filters is shown to be crucial if low BER is required. Data-aided channel estimation is shown to be more robust than decision-directed channel estimation, which may suffer from BER saturation caused by hang-ups at high signal-to-noise ratios. Multiuser receivers for dynamic CDMA systems are studied. Algorithms for ideal linear detector computation are derived and their complexity is analyzed. The complexity of the linear detector computation is a cubic function of KL, where K and L are the number of users and multipath components, respectively. Iterative steepest descent, conjugate gradient, and preconditioned conjugate gradient algorithms are proposed to reduce the complexity. The computational requirements for one iteration are a quadratic function of KL. The iterative detectors are also shown to be applicable for parallel implementation. Simulation results demonstrate that a moderate number of iterations yields the performance of the corresponding ideal linear detectors. A quantitative analysis shows that the PIC receivers are significantly simpler to implement than the linear receivers and only moderately more complex than the conventional matched filter bank receiver.

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Multiuser demodulation for DS-CDMA systems in fading channels

This survey paper reviews space-time signal processing (STP) in mobile wireless communications. Space-time processing refers to manipulating signals that are received at or transmitted from an antenna array so as to improve performance. We focus on antenna arrays deployed at the base stations since such applications are of current practical interest. We first introduce channel and signal models for base station antennas, and present the different structures present in the channel model after sampling and stacking the received signals. We then present single user (SU) and multiple user (MU) space-time processing techniques for the reverse link. Our focus is on blind signal separation, and intersymbol/co-channel interference cancellation. We consider a number of recent advances in batch and adaptive blind space-time processing that show promise in solving these problems.

Space-time signal processing for wireless communications: a survey

A co-channel system can be viewed as a multiple-input, multiple-output communication system. By extending the scalar constant-modulus algorithm to vector-valued signals, we develop several methods for blind cancellation of co-channel interference. In particular, to prevent the receiver from locking on to the same signal more than once, we propose the determinant constant-modulus algorithm. For the special case of constant-modulus signals and a memoryless channel, this method can outperform other known methods, as demonstrated by simulation.

Blind cancellation of co-channel interference

We present a new technique for blind equalization of multiple-input multiple-output (MIMO) communication channels. In scalar channels it is common to follow a blind equalizer adapted according to the constant-modulus algorithm (CMA) by a phase-locked loop to compensate for carrier frequency offset. We generalize this structure to multiple dimensions, and propose to follow a blind MIMO equalizer adapted according to the vector CMA by a multidimensional phase-locked loop. We show through simulations that the new technique can converge much faster than prior techniques.

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A multidimensional phase-locked loop for blind equalization of multi-input multi-output channels

Blind source separation cannot generally be performed using second-order statistics alone because of a unitary matrix ambiguity. We present the multidimensional phase-locked loop (MPLL) as a blind algorithm for resolving this ambiguity. The MPLL is a multidimensional generalization of the scalar decision-directed PLL for resolving phase rotations in scalar digital communication systems, and as such is applicable only to discrete-alphabet sources. We compare the MPLL to other known unitary source separation algorithms, and find that the MPLL compares favorably in terms of both performance and complexity.

Blind unitary source separation using a multidimensional phase-locked loop

This paper concerns the problem of blind multiuser detection, a special case of the blind source separation problem in which the source signals have finite alphabets. Specifically, we address the problem of identifying and resolving the n/spl times/n unitary matrix ambiguity U that results from whitening the receiver observations, where n is the number of sources. We propose the multidimensional phase-locked loop (MPLL) as a generalization of a scalar decision-directed PLL to vector-valued signals. The MPLL adapts an estimate of U according to the recursion U/spl circ//sub k+1/=U/spl circ//sub k/R/sub k/, where R/sub k/ is an n-dimensional Householder-like rotation depending on only the kth receiver observation. The O(n/sup 2/) complexity of an efficient implementation of the algorithm is extremely low. Nevertheless, simulation results demonstrate good convergence properties and superior steady-state performance when compared with prior techniques. The algorithm is also able to accommodate large alphabets and shaped alphabets.

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A. Batra

Papers

Blind cancellation of co-channel interference

A multidimensional phase-locked loop for blind equalization of multi-input multi-output channels

Blind unitary source separation using a multidimensional phase-locked loop

A multidimensional phase-locked loop for blind multiuser detection