An adaptive step-size code-constrained minimum output energy receiver for nonstationary CDMA channels

The adaptive step-size (AS) code-constrained minimum output energy (CMOE) receiver for nonstationary code-division multiple access (CDMA) channels is proposed. The AS-CMOE algorithm adaptively varies the step-size in order to minimise the CMOE criterion. Admissibility of the proposed method is confirmed via the reformulation of the CMOE criterion as an unconstrained optimisation. The ability of the algorithm to track sudden changes of the channel structure in multipath fading channels is assessed. Sensitivity to the initial values of the step-size and the adaptation rate of the algorithm is also investigated

Adaptive step-size blind multi-user detectors for DS-CDMA systems under deterministically and Markovian time-varying multipath environments

Published versio

Blind adaptive near-far resistant receivers for DS/CDMA multi-user communication systems

Code-division multiple-access (CDMA) systems have multiple users that simultaneously share a common channel using pre-assigned signature waveforms. The conventional receiver suffers from the near-far problem when the received signal power of the desired user is weaker than those of the other users. Optimum and suboptimum multi-user detectors outperform the conventional receiver at the expense of a significant increase in complexity and need for side-information about interfering users. Complexity of these detectors may not be acceptable for many practical applications and communication security may restrict the distribution of all users\u27 signature waveforms to all the receivers;For a single-user receiver, the multi-user detection problem is viewed as an interference suppression problem. This dissertation presents a cost-constraint strategy to implement adaptive single-user receivers that suppress the multiple-access interference without using training sequences. A constrained LMS algorithm that converges to a near-optimum solution by using the received signal and some known properties of the desired signal is developed. The constrained LMS receiver is useful for static CDMA detection where the channel accessed by the desired user is time-invariant. The dissertation also develops an adaptive space-alternating generalized EM (SAGE) algorithm. This algorithm jointly updates estimates of filter weights and adaptive reference signal in a sequential manner. The SAGE receiver out-performs the existing: blind receiver that employ the constrained output-power-minimizing algorithm while using the same amount of information. The SAGE receiver is applicable to dynamic CDMA detection where the channel accessed by the desired user is time-varying. The dissertation further generalizes the adaptive SAGE algorithm to an adaptive space-alternating generalized projection (SAGP) algorithm that uses the same amount of information as in the conventional receiver;Proposed receivers are tested by simulations and compared with the existing receivers that use the same amount of information. Throughout the analytical analysis and simulations of the proposed receivers, the dissertation shows that, for realistic CDMA communications, achieving both the near-far resistance and the near-optimum performance is possible with the same or similar information required by the conventional receiver

Linearly Constrained RLS Algorithm with Variable Forgetting Factor for DS-CDMA Systems

[[abstract]]In this paper we present a novel linearly constrained (LC) RLS algorithm with variable forgetting factor (VFF), and apply to the DS-CDMA system for suddenly joined narrowband interference suppression. Under Rayleigh fading channel environment, the VFF could be employed to improve the tracking capability compared with the conventional LC-RLS algorithm with fixed value of forgetting factor (FF). From computer simulation results, we verify that the proposed scheme outperforms the conventional optimal FF LC-RLS algorithm in terms of rapid tracking capability and strong narrow-band suppression.[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]2014 12 01~2014 12 04[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Kuching , Sarawak, Malaysia (古晉, 馬來西亞

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

Constrained Linear and Non-Linear Adaptive Equalization Techniques for MIMO-CDMA Systems

Researchers have shown that by combining multiple input multiple output (MIMO) techniques with CDMA then higher gains in capacity, reliability and data transmission speed can be attained. But a major drawback of MIMO-CDMA systems is multiple access interference (MAI) which can reduce the capacity and increase the bit error rate (BER), so statistical analysis of MAI becomes a very important factor in the performance analysis of these systems. In this thesis, a detailed analysis of MAI is performed for binary phase-shift keying (BPSK) signals with random signature sequence in Raleigh fading environment and closed from expressions for the probability density function of MAI and MAI with noise are derived. Further, probability of error is derived for the maximum Likelihood receiver. These derivations are verified through simulations and are found to reinforce the theoretical results. Since the performance of MIMO suffers significantly from MAI and inter-symbol interference (ISI), equalization is needed to mitigate these effects. It is well known from the theory of constrained optimization that the learning speed of any adaptive filtering algorithm can be increased by adding a constraint to it, as in the case of the normalized least mean squared (NLMS) algorithm. Thus, in this work both linear and non-linear decision feedback (DFE) equalizers for MIMO systems with least mean square (LMS) based constrained stochastic gradient algorithm have been designed. More specifically, an LMS algorithm has been developed , which was equipped with the knowledge of number of users, spreading sequence (SS) length, additive noise variance as well as MAI with noise (new constraint) and is named MIMO-CDMA MAI with noise constrained (MNCLMS) algorithm. Convergence and tracking analysis of the proposed algorithm are carried out in the scenario of interference and noise limited systems, and simulation results are presented to compare the performance of MIMO-CDMA MNCLMS algorithm with other adaptive algorithms

Interference cancellation for shot-code DS-CDMA in the presence of channel fading

Interference from other adjacent users in wireless applications is a major problem in direct-sequence code-division multiple-access (DS-CDMA). This is also known as the near-far problem where a strong signal from one user interferes with other users. The current approach to deal with the near-far problem in DS-CDMA systems is to use strict transmitter power control. An alternative approach is to use near-far resistant receivers. The practical near-far resistance receiver structure is the adaptive decorrelating detectors since it avoids complex matrix inversion. The existing CDMA standard known as IS-95 uses a long signature code sequence. However for simplicity, the adaptive multi-user receiver uses short signature code sequence. The problem is that adaptive receivers lose near-far resistance as the number of users increases in the system. This thesis describes a novel method of multistage decision feedback cancellation (DFC) scheme immune from the near-far problem. The performance of the new DFC structure is constructed using three different adaptive algorithms: the least mean squared (LMS), the recursive least squared (RLS) and the linearly constraint constant modulus (LCCM) adaptive algorithms. It is found that LMS adaptive algorithm provides the best result considering its simple hardware complexity. It is also found that the LMS adaptive receiver along with the DFC structure provides a better bit synchronization capability to the over all system. Since the receiver is near-far resistant, the LMS adaptive receiver along with the decision feedback cancellation structure also performs better in the presence of Rayleigh fading