Blind adaptive constrained reduced-rank parameter estimation based on constant modulus design for CDMA interference suppression

This paper proposes a multistage decomposition for blind adaptive parameter estimation in the Krylov subspace with the code-constrained constant modulus (CCM) design criterion. Based on constrained optimization of the constant modulus cost function and utilizing the Lanczos algorithm and Arnoldi-like iterations, a multistage decomposition is developed for blind parameter estimation. A family of computationally efficient blind adaptive reduced-rank stochastic gradient (SG) and recursive least squares (RLS) type algorithms along with an automatic rank selection procedure are also devised and evaluated against existing methods. An analysis of the convergence properties of the method is carried out and convergence conditions for the reduced-rank adaptive algorithms are established. Simulation results consider the application of the proposed techniques to the suppression of multiaccess and intersymbol interference in DS-CDMA systems

Asynchronous CDMA Systems with Random Spreading-Part II: Design Criteria

Totally asynchronous code-division multiple-access (CDMA) systems are addressed. In Part I, the fundamental limits of asynchronous CDMA systems are analyzed in terms of spectral efficiency and SINR at the output of the optimum linear detector. The focus of Part II is the design of low-complexity implementations of linear multiuser detectors in systems with many users that admit a multistage representation, e.g. reduced rank multistage Wiener filters, polynomial expansion detectors, weighted linear parallel interference cancellers. The effects of excess bandwidth, chip-pulse shaping, and time delay distribution on CDMA with suboptimum linear receiver structures are investigated. Recursive expressions for universal weight design are given. The performance in terms of SINR is derived in the large-system limit and the performance improvement over synchronous systems is quantified. The considerations distinguish between two ways of forming discrete-time statistics: chip-matched filtering and oversampling

Interference suppression and diversity for CDMA systems

In code-division multiple-access (CDMA) systems, due to non-orthogonality of the spreading codes and multipath channels, the desired signal suffers interference from other users. Signal fading due to multipath propagation is another source of impairment in wireless CDMA systems, often severely impacting performance. In this dissertation, reduced-rank minimum mean square error (MMSE) receiver and reduced-rank minimum variance receiver are investigated to suppress interference; transmit diversity is applied to multicarrier CDMA (MC-CDMA) systems to combat fading; packet combing is studied to provide both interference suppression and diversity for CDMA random access systems. The reduced-rank MMSE receiver that uses a reduced-rank estimated covariance matrix is studied to improve the performance of MMSE receiver in CDMA systems. It is shown that the reduced-rank MMSE receiver has much better performance than the full-rank MMSE receiver when the covariance matrix is estimated by using a finite number of data samples and the desired signal is in a low dimensional subspace. It is also demonstrated that the reduced-rank minimum variance receiver outperforms the full-rank minimum variance receiver. The probability density function of the output SNR of the full-rank and reduced-rank linear MMSE estimators is derived for a general linear signal model under the assumption that the signals and noise are Gaussian distributed. Space-time coding that is originally proposed for narrow band systems is applied to an MC-CDMA system in order to get transmit diversity for such a wideband system. Some techniques to jointly decode the space-time code and suppress interference are developed. The channel estimation using either pilot channels or pilot symbols is studied for MC-CDMA systems with space-time coding. Performance of CDMA random access systems with packet combining in fading channels is analyzed. By combining the current retransmitted packet with all its previous transmitted copies, the receiver obtains a diversity gain plus an increased interference and noise suppression gain. Therefore, the bit error rate dramatically decreases with the number of transmissions increasing, which in turn improves the system throughput and reduces the average delay

Adaptive DS-CDMA multiuser detection for time variant frequency selective Rayleigh fading channel

The current digital wireless mobile system such as IS-95, which is based on direct sequence Code Division Multiple Access (DS-CDMA) technology, will not be able to meet the growing demands for multimedia service due to low information exchanging rate. Its capacity is also limited by multiple accessed interference (MAI) signals. This work focuses on the development of adaptive algorithms for multiuser detection (MUD) and interference suppression for wideband direct sequence code division multiple access (DS-CDMA) systems over time-variant frequency selective fading channels. In addition, channel acquisition and delay estimation techniques are developed to combat the uncertainty introduced by the wireless propagation channel. This work emphasizes fast and simple techniques that can meet practical needs for high data rate signal detection. Most existing literature is not suitable for the large delay spread in wideband systems due to high computational/ hardware complexity. A de-biasing decorrelator is developed whose computational complexity is greatly reduced without sacrificing performance. An adaptive bootstrap symbolbased signal separator is also proposed for a time-variant channel. These detectors achieve MUD for asynchronous, large delay spread, fading channels without training sequences. To achieve high data rate communication, a finite impulse response (FIR) filter based detector is presented for M-ary QAM modulated signals in a multipath Rayleigh fading channel. It is shown that the proposed detector provides a stable performance for QAM signal detection with unknown fading and phase shift. It is also shown that this detector can be easily extended to the reception of any M-ary quadrature modulated signal. A minimum variance decorrelating (MVD) receiver with adaptive channel estimator is presented in this dissertation. It provides comparable performance to a linear MMSE receiver even in a deep fading environment and can be implemented blindly. Using the MVD receiver as a building-block, an adaptive multistage parallel interference cancellation (PIC) scheme and a successive interference cancellation (SIC) scheme were developed. The total number of stages is kept at a minimum as a result of the accurate estimating of the interfering users at the earliest stages, which reduces the implementation complexity, as well as the processing delay. Jointly with the MVD receiver, a new transmit diversity (TD) scheme, called TD-MVD, is proposed. This scheme improves the performance without increasing the bandwidth. Unlike other TD techniques, this TDMVD scheme has the inherent advantage to overcome asynchronous multipath transmission. It brings flexibility in the design of TD antenna systems without restrict signal coordination among those multiple transmissions, and applicable for both existing and next generation of CDMA systems. A maximum likelihood based delay and channel estimation algorithm with reduced computational complexity is proposed. This algorithm uses a diagonal simplicity technique as well as the asymptotically uncorrelated property of the received signal in the frequency domain. In combination with oversampling, this scheme does not suffer from a singularity problem and the performance quickly approaches the Cramer-Rao lower bound (CRLB) while maintaining a computational complexity that is as low as the order of the signal dimension

Robust Reduced-Rank Adaptive Processing Based on Parallel Subgradient Projection and Krylov Subspace Techniques

In this paper, we propose a novel reduced-rank adaptive filtering algorithm by blending the idea of the Krylov subspace methods with the set-theoretic adaptive filtering framework. Unlike the existing Krylov-subspace-based reduced-rank methods, the proposed algorithm tracks the optimal point in the sense of minimizing the \sinq{true} mean square error (MSE) in the Krylov subspace, even when the estimated statistics become erroneous (e.g., due to sudden changes of environments). Therefore, compared with those existing methods, the proposed algorithm is more suited to adaptive filtering applications. The algorithm is analyzed based on a modified version of the adaptive projected subgradient method (APSM). Numerical examples demonstrate that the proposed algorithm enjoys better tracking performance than the existing methods for the interference suppression problem in code-division multiple-access (CDMA) systems as well as for simple system identification problems.Comment: 10 figures. In IEEE Transactions on Signal Processing, 201