Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems

In this work, decision feedback (DF) detection algorithms based on multiple processing branches for multi-input multi-output (MIMO) spatial multiplexing systems are proposed. The proposed detector employs multiple cancellation branches with receive filters that are obtained from a common matrix inverse and achieves a performance close to the maximum likelihood detector (MLD). Constrained minimum mean-squared error (MMSE) receive filters designed with constraints on the shape and magnitude of the feedback filters for the multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive implementation of the proposed MB-MMSE-DF detector is developed along with a recursive least squares-type algorithm for estimating the parameters of the receive filters when the channel is time-varying. A soft-output version of the MB-MMSE-DF detector is also proposed as a component of an iterative detection and decoding receiver structure. A computational complexity analysis shows that the MB-MMSE-DF detector does not require a significant additional complexity over the conventional MMSE-DF detector, whereas a diversity analysis discusses the diversity order achieved by the MB-MMSE-DF detector. Simulation results show that the MB-MMSE-DF detector achieves a performance superior to existing suboptimal detectors and close to the MLD, while requiring significantly lower complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications, 201

Investigation of non-binary trellis codes designed for impulsive noise environments

PhD ThesisIt is well known that binary codes with iterative decoders can achieve near Shannon limit performance on the additive white Gaussian noise (AWGN) channel, but their performance on more realistic wired or wireless channels can become degraded due to the presence of burst errors or impulsive noise. In such extreme environments, error correction alone cannot combat the serious e ect of the channel and must be combined with the signal processing techniques such as channel estimation, channel equalisation and orthogonal frequency division multiplexing (OFDM). However, even after the received signal has been processed, it can still contain burst errors, or the noise present in the signal maybe non Gaussian. In these cases, popular binary coding schemes such as Low-Density Parity-Check (LDPC) or turbo codes may not perform optimally, resulting in the degradation of performance. Nevertheless, there is still scope for the design of new non-binary codes that are more suitable for these environments, allowing us to achieve further gains in performance. In this thesis, an investigation into good non-binary trellis error-correcting codes and advanced noise reduction techniques has been carried out with the aim of enhancing the performance of wired and wireless communication networks in di erent extreme environments. These environments include, urban, indoor, pedestrian, underwater, and powerline communication (PLC). This work includes an examination of the performance of non-binary trellis codes in harsh scenarios such as underwater communications when the noise channel is additive S S noise. Similar work was also conducted for single input single output (SISO) power line communication systems for single carrier (SC) and multi carrier (MC) over realistic multi-path frequency selective channels. A further examination of multi-input multi-output (MIMO) wired and wireless systems on Middleton class A noise channel was carried out. The main focus of the project was non-binary coding schemes as it is well-known that they outperform their binary counterparts when the channel is bursty. However, few studies have investigated non-binary codes for other environments. The major novelty of this work is the comparison of the performance of non-binary trellis codes with binary trellis codes in various scenarios, leading to the conclusion that non-binary codes are, in most cases, superior in performance to binary codes. Furthermore, the theoretical bounds of SISO and MIMO binary and non-binary convolutional coded OFDM-PLC systems have been investigated for the rst time. In order to validate our results, the implementation of simulated and theoretical results have been obtained for di erent values of noise parameters and on di erent PLC channels. The results show a strong agreement between the simulated and theoretical analysis for all cases.University of Thi-Qar for choosing me for their PhD scholarship and the Iraqi Ministry of Higher Education and Scienti c Research (MOHESR) for granting me the funds to study in UK. In addition, there was ample support towards my stay in the UK from the Iraqi Cultural Attach e in Londo

Turbo codes and turbo algorithms

In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding

Channel Estimation in Coded Modulation Systems

With the outstanding performance of coded modulation techniques in fading channels, much research efforts have been carried out on the design of communication systems able to operate at low signal-to-noise ratios (SNRs). From this perspective, the so-called iterative decoding principle has been applied to many signal processing tasks at the receiver: demodulation, detection, decoding, synchronization and channel estimation. Nevertheless, at low SNRs, conventional channel estimators do not perform satisfactorily. This thesis is mainly concerned with channel estimation issues in coded modulation systems where different diversity techniques are exploited to combat fading in single or multiple antenna systems. First, for single antenna systems in fast time-varying fading channels, the thesis focuses on designing a training sequence by exploiting signal space diversity (SSD). Motivated by the power/bandwidth efficiency of the SSD technique, the proposed training sequence inserts pilot bits into the coded bits prior to constellation mapping and signal rotation. This scheme spreads the training sequence during a transmitted codeword and helps the estimator to track fast variation of the channel gains. A comprehensive comparison between the proposed training scheme and the conventional training scheme is then carried out, which reveals several interesting conclusions with respect to both error performance of the system and mean square error of the channel estimator. For multiple antenna systems, different schemes are examined in this thesis for the estimation of block-fading channels. For typical coded modulation systems with multiple antennas, the first scheme makes a distinction between the iteration in the channel estimation and the iteration in the decoding. Then, the estimator begins iteration when the soft output of the decoder at the decoding iteration meets some specified reliability conditions. This scheme guarantees the convergence of the iterative receiver with iterative channel estimator. To accelerate the convergence process and decrease the complexity of successive iterations, in the second scheme, the channel estimator estimates channel state information (CSI) at each iteration with a combination of the training sequence and soft information. For coded modulation systems with precoding technique, in which a precoder is used after the modulator, the training sequence and data symbols are combined using a linear precoder to decrease the required training overhead. The power allocation and the placement of the training sequence to be precoded are obtained based on a lower bound on the mean square error of the channel estimation. It is demonstrated that considerable performance improvement is possible when the training symbols are embedded within data symbols with an equi-spaced pattern. In the last scheme, a joint precoder and training sequence is developed to maximize the achievable coding gain and diversity order under imperfect CSI. In particular, both the asymptotic performance behavior of the system with the precoded training scheme under imperfect CSI and the mean square error of the channel estimation are derived to obtain achievable diversity order and coding gain. Simulation results demonstrate that the joint optimized scheme outperforms the existing training schemes for systems with given precoders in terms of error rate and the amount of training overhead