Turbo Decoding and Detection for Wireless Applications

A historical perspective of turbo coding and turbo transceivers inspired by the generic turbo principles is provided, as it evolved from Shannon’s visionary predictions. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannon’s capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated spacetime and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted

Reduced Complexity Neural Network Equalizers for Two-dimensional Magnetic Recording

This paper investigates reduced complexity neural network (NN) based architectures for equalization over the two-dimension magnetic recording (TDMR) digital communication channel for data storage. We use realistic waveforms measured from a hard disk drive (HDD) with TDMR technology. We show that the multilayer perceptron (MLP) non-linear equalizer achieves a $10.91\%$ reduction in bit error rate (BER) over the linear equalizer with cross-entropy-based optimization. However, the MLP equalizer's complexity is $6.6$ times the linear equalizer's complexity. Thus, we propose reduced complexity MLP (RC-MLP) equalizers. Each RC-MLP variant consists of finite-impulse response filters, a non-linear activation, and a hidden delay line. A proposed RC-MLP variant entails only $1.59$ times the linear equalizer's complexity while achieving a $8.23\%$ reduction in BER over the linear equalizer.Comment: This paper has been accepted for publication in IEEE Transactions on Magnetics. Part of this paper was presented in the 33rd magnetic recording conference (TMRC) 2022, on August 29, 202

MMSE equalizers and precoders in turbo equalization.

Thesis (M.Sc.Eng.)-University of Natal, Durban, 2003.Transmission of digital information through a wireless channel with resolvable multipaths or a bandwidth limited channel results in intersymbol interference (1SI) among a number of adjacent symbols. The design of an equalizer is thus important to combat the ISI problem for these types of channels and hence provides reliable communication. Channel coding is used to provide reliable data transmission by adding controlled redundancy to the data. Turbo equalization (TE) is the joint design of channel coding and equalization to approach the achievable uniform input information rate of an ISI channel. The main focus of this dissertation is to investigate the different TE techniques used for a static frequency selective additive white Gaussian noise (AWGN) channel. The extrinsic information transfer (EXIT) chart is used to analyse the iterative equalization/decoding process and to determine the minimum signal to noise ratio (SNR) in order to achieve convergence. The use of the Minimum Mean Square Error (MMSE) Linear Equalizer (LE) using a priori information has been shown to achieve the same performance compared with the optimal trellis based Maximum A Posterior (MAP) equalizer for long block lengths. Motivated by improving the performance of the MMSE LE, two equalization schemes are initially proposed: the MMSE Linear Equalizer with Extrinsic information Feedback (LE-EF (1) and (U)). A general structure for the MMSE LE, MMSE Decision Feedback Equalizer (DFE) and two MMSE LE-EF receivers, using a priori information is also presented. The EXIT chart is used to analyse the two proposed equalizers and their characteristics are compared to the existing MAP equalizer, MMSE LE and MMSE DFE. It is shown that the proposed MMSE LE-EF (1) does have an improved performance compared with the existing MMSE LE and approaches the MMSE Linear Equalizer with Perfect Extrinsic information Feedback (LE-PEF) only after a large number of iterations. For this reason the MMSE LE-EF is shown to suffer from the error propagation problem during the early iterations. A novel way to reduce the error propagation problem is proposed to further improve the performance of the MMSE LE-EF (I). The MAP equalizer was shown to offer a much improved performance over the MMSE equalizers, especially during the initial iterations. Motivated by using the good quality of the MAP equalizer during the early iterations and the hybrid MAP/MMSE LE-EF (l) is proposed in order to suppress the error propagation problem inherent in the MMSE LE-EF (I). The EXIT chart analysis reveals that the hybrid MAP/MMSE LE-EF (l) requires fewer iterations in order to achieve convergence relative to the MMSE LE-EF (l). Simulation results demonstrate that the hybrid MAP/MMSE LE-EF (I) has a superior performance compared to the MMSE LE-EF (I) as well as approaches the performance of both the MAP equalizer and MMSE LE-PEF at high SNRs, at the cost of increased complexity relative to the MMSE LEEF (I) receiver. The final part of this dissertation considers the use of precoders in a TE system. It was shown in the literature that a precoder drastically improves the system performance. Motivated by this, the EXIT chart is used to analyse the characteristics of four different precoders for long block lengths. It was shown that using a precoder results in a loss in mutual information during the initial equalization stage. However" we show by analysis and simulations that this phenomenon is not observed in the equalization of all precoded channels. The slope of the transfer function, relating to the MAP equalization of a precoded ISI channel (MEP), during the high input mutual information values is shown to play an important role in determining the convergence of precoded TE systems. Simulation results are presented to show how the precoders' weight affects the convergence of TE systems. The design of the hybrid MAP/MEP equalizer is also proposed. We also show that the EXIT chart can be used to compute the trellis code capacity of a precoded ISI channel

Low complexity turbo equalization for coded intersymbol interference channels

Master'sMASTER OF ENGINEERIN

Turbo-Coded Adaptive Modulation Versus Space-Time Trellis Codes for Transmission over Dispersive Channels

Decision feedback equalizer (DFE)-aided turbocoded wideband adaptive quadrature amplitude modulation (AQAM) is proposed, which is capable of combating the temporal channel quality variation of fading channels. A procedure is suggested for determining the AQAM switching thresholds and the specific turbo-coding rates capable of maintaining the target bit-error rate while aiming for achieving a highly effective bits per symbol throughput. As a design alternative, we also employ multiple-input/multiple-output DFE-aided space–time trellis codes, which benefit from transmit diversity and hence reduce the temporal channel quality fluctuations. The performance of both systems is characterized and compared when communicating over the COST 207 typical urban wideband fading channel. It was found that the turbo-coded AQAM scheme outperforms the two-transmitter space–time trellis coded system employing two receivers; although, its performance is inferior to the space–time trellis coded arrangement employing three receivers. Index Terms—Coded adaptive modulation, dispersive channels, space–time trellis codes

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems