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

On Development of Some Soft Computing Based Multiuser Detection Techniques for SDMA–OFDM Wireless Communication System

Space Division Multiple Access(SDMA) based technique as a subclass of Multiple Input Multiple Output (MIMO) systems achieves high spectral efficiency through bandwidth reuse by multiple users. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) mitigates the impairments of the propagation channel. The combination of SDMA and OFDM has emerged as a most competitive technology for future wireless communication system. In the SDMA uplink, multiple users communicate simultaneously with a multiple antenna Base Station (BS) sharing the same frequency band by exploring their unique user specific-special spatial signature. Different Multiuser Detection (MUD) schemes have been proposed at the BS receiver to identify users correctly by mitigating the multiuser interference. However, most of the classical MUDs fail to separate the users signals in the over load scenario, where the number of users exceed the number of receiving antennas. On the other hand, due to exhaustive search mechanism, the optimal Maximum Likelihood (ML) detector is limited by high computational complexity, which increases exponentially with increasing number of simultaneous users. Hence, cost function minimization based Minimum Error Rate (MER) detectors are preferred, which basically minimize the probability of error by iteratively updating receiver’s weights using adaptive algorithms such as Steepest Descent (SD), Conjugate Gradient (CG) etc. The first part of research proposes Optimization Techniques (OTs) aided MER detectors to overcome the shortfalls of the CG based MER detectors. Popular metaheuristic search algorithms like Adaptive Genetic Algorithm (AGA), Adaptive Differential Evolution Algorithm (ADEA) and Invasive Weed Optimization (IWO), which rely on an intelligent search of a large but finite solution space using statistical methods, have been applied for finding the optimal weight vectors for MER MUD. Further, it is observed in an overload SDMA–OFDM system that the channel output phasor constellation often becomes linearly non-separable. With increasing the number of users, the receiver weight optimization task turns out to be more difficult due to the exponentially increased number of dimensions of the weight matrix. As a result, MUD becomes a challenging multidimensional optimization problem. Therefore, signal classification requires a nonlinear solution. Considering this, the second part of research work suggests Artificial Neural Network (ANN) based MUDs on thestandard Multilayer Perceptron (MLP) and Radial Basis Function (RBF) frameworks fo

Performance Evaluation of Phase Optimized Spreading Codes in Non Linear DS-CDMA Receiver

Spread spectrum (SS) is a modulation technique in which the signal occupies a bandwidth much larger than the minimum necessary to send the information. A synchronized reception with the code at the receiver is used for despreading the information before data recovery. Bandspread is accomplished by means of a code which is independent of the data. Bandspreading code is pseudo-random, thus the spread signal resembles noise. The coded modulation characteristic of SS system uniquely qualifies it for navigation applications. Any signal used in ranging is subject to time/distance relations. A SS signal has advantage that its phase is easily resolvable. Direct-sequence (DS) form of modulation is mostly preferred over Frequency Hopping system (FH) as FH systems do not normally possess high resolution properties. Higher the chip rate, the better the measurement capability. The basic resolution is one code chip. Initially, some existing code families e.g. Gold, Kasami (large and smal..

Nonlinear receivers for DS-CDMA

The growing demand for capacity in wireless communications is the driving force behind improving established networks and the deployment of a new worldwide mobile standard. Capacity calculations show that the direct sequence code division multiple access (DS-CDMA) technique has more capacity than the time division multiple access technique. Therefore, most 3rd generation mobile systems will incorporate some sort of DS-CDMA. In this thesis DS-CDMA receiver structures are investigated from the view point of pattern recognition which leads to new DS-CDMA receiver structures. It is known that the optimum DS-CDMA receiver has a nonlinear structure with prohibitive complexity for practical implementation. It is also known that the currently implemented receiver in 2nd generation DSCDMA mobile handsets has poor performance, because it suffers from multiuser interference. Consequently, this work focuses on sub-optimum nonlinear receivers for DS-CDMA in the downlink scenario. First, the thesis reviews DS-CDMA, established equalisers, DS-CDMA receivers and pattern recognition techniques. Then the new receivers are proposed. It is shown that DS-CDMA can be considered as a pattern recognition problem and hence, pattern recognition techniques can be exploited in order to develop DS-CDMA receivers. Another approach is to apply known equaliser structures for DS-CDMA. One proposed receiver is based on the Volterra series expansion and processes the received signal at the chip rate. Another receiver is a symbol rate radial basis function network (RBFN) receiver with reduced complexity. Subsequently, a receiver is proposed based on linear programming (LP) which is especially tailored for nonlinearly separable scenarios. The LP based receiver performance is equivalent to the known decorrelating detector in linearly separable scenarios. Finally, a hybrid receiver is proposed which combines LP and RBFN and which exploits knowledge gained from pattern recognition. This structure has lower complexity than the full RBF and good performance, and has a large potential for further improvements. Monte-Carlo simulations compare the proposed DS-CDMA receivers against established linear and nonlinear receivers. It is shown that all proposed receivers outperform the known linear receivers. The Volterra receiver’s complexity is relatively high for the performance gain achieved and might not suit practical implementation. The other receiver’s complexity was greatly reduced but it performs nearly as well as an optimum symbol by symbol detector. This thesis shows that DS-CDMA is a pattern recognition problem and that pattern recognition techniques can simplify DS-CDMA receiver structures. Knowledge is gained from the DSCDMA signal patterns which help to understand the problem of a DS-CDMA receiver. It should be noted that from the large number of known techniques, only a few pattern recognition techniques are considered in this work, and any further work should look at other techniques. Pattern recognition techniques can reduce the complexity of existing DS-CDMA receivers while maintaining performance, leading to novel receiver structures

Interference mitigation using group decoding in multiantenna systems

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Iterative multiuser receivers for coded DS-CDMA systems

The introduction of cellular wireless systems in the 1980s has resulted in a continuous and growing demand for personal communication services. This demand has made larger capacity systems necessary. With the interest from both the research community and industry in wireless code-division multiple-access (CDMA) systems, the application of multiuser detection (MUD) techniques to wireless systems is becoming increasingly important. MUD is an important area of interest to help obtain the significant increase in capacity needed for future wireless services. The standardisation of direct-sequence CDMA (DS-CDMA) systems in the third generation of mobile communication systems has raised even more interest in exploiting the capabilities and capacity of this type of technology. However, the conventional DS-CDMA system has the major problem of multiple-access interference (MAI). The MAI is unavoidable because receivers deal with information which is transmitted not by a single source but by several uncoordinated and geographically separated sources. As a result, the capacity of these systems is inherently interference limited by other users. To overcome these limitations, MUD emerges as a promising approach to increase the system capacity. This thesis addresses the problem of improving the downlink capacity of a coded DS-CDMA system with the use of MUD techniques at the mobile terminal receiver. The optimum multiuser receiver scheme is far too computational intensive for practical use. Therefore, the aim of this thesis is to investigate sub-optimal multiuser receiver schemes that can exploit the advantages of MUD but also simplify its implementation. The attention is primarily focused on iterative MUD receiver schemes which apply the turbo multiuser detection principle. Essentially this principle consists of an iterative exchange of extrinsic information among the receiver modules to achieve improved performance. In this thesis, the implementation of an iterative receiver based on a linear MUD technique and a cancellation scheme over an additive white Gaussian noise (AWGN) channel is first proposed and analysed. The interference analysis shows that good performance is achieved using a lowcomplexity receiver structure. In more realistic mobile channels, however, this type of receiver suffers from the presence of higher levels of interference resulting in poor receiver performance. The reason for this is that in such scenarios the desired signals are no longer linearly separable. Therefore, non-linear detection techniques are required to provide better performance. With this purpose, a hybrid iterative multiuser receiver is investigated for the case of a stationary multipath channel. The incorporation of antenna arrays is an effective and practical technique to provide a significant capacity gain over conventional single-antenna systems. In this context, a novel space-time iterative multiuser receiver is proposed which achieves a large improvement in spectral efficiency and performance over multipath fading channels. In addition, it is shown that this architecture can be implemented without a prohibitive complexity cost. The exploitation of the iterative principle can be used to approach the capacity bounds of a coded DS-CDMA system. Using the Shannon’s sphere packing bound, a comparison is presented to illustrate how closely a practical system can approach the theoretical limits of system performance

Near maximum likelihood multiuser receivers for direct sequence code division multiple access

Wideband wireless access based on direct-sequence code-division multiple access (DS-CDMA) has been adopted for third-generation mobile communications systems. Hence, DS-CDMA downlink communications systems form the platform for the work in this thesis. The principles of the spread spectrum concept and DS-CDMA technology are first outlined, including a description of the system model and the conventional receiver. The two classes of codes used in this system, namely spreading codes and forward error correction codes (including Turbo codes), are discussed. Due to the fact that practical communications channels are non-ideal, the performance of an individual user is interference limited. As a result, the capacity of the system is greatly restricted. Fortunately, multiuser detection is a scheme that can effectively counteract this multiple access interference. However, the optimum multiuser detection scheme is far too computationally intensive for practical use. Hence, the fundamental interest here is to retain the advantages of multiuser detection and simplify its implementation. The objective of the thesis is to investigate the optimum multiuser receiver, regarded on a chip level sampling basis. The aim is to reduce the complexity of the optimum receiver to a practical and implementable level while retaining its good performance. The thesis first reviews various existing multiuser receivers. The chip-based maximum likelihood sequence estimation (CBMLSE) detector is formulated and implemented. However, the number of states in the state-transition trellis is still exponential in the number of users. Complexity cannot be reduced substantially without changing the structure of the trellis. A new detector is proposed which folds up the original state-transition trellis such that the number of states involved is greatly reduced. The performance is close to that of the CBMLSE. The folded trellis detector (FTD) can also be used as a preselection stage for the CBMLSE. The FTD selects with high accuracy the few symbol vectors that are more likely to be transmitted. The CBMLSE is then used to determine the most likely symbol vector out of the small subset of vectors. The performance of this scheme is as good as the CBMLSE. The FTD is also applied in an iterative multiuser receiver that exploits the powerful iterative algorithm of Turbo codes

Multiuser detection employing recurrent neural networks for DS-CDMA systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2006.Over the last decade, access to personal wireless communication networks has evolved to a point of necessity. Attached to the phenomenal growth of the telecommunications industry in recent times is an escalating demand for higher data rates and efficient spectrum utilization. This demand is fuelling the advancement of third generation (3G), as well as future, wireless networks. Current 3G technologies are adding a dimension of mobility to services that have become an integral part of modem everyday life. Wideband code division multiple access (WCDMA) is the standardized multiple access scheme for 3G Universal Mobile Telecommunication System (UMTS). As an air interface solution, CDMA has received considerable interest over the past two decades and a great deal of current research is concerned with improving the application of CDMA in 3G systems. A factoring component of CDMA is multiuser detection (MUD), which is aimed at enhancing system capacity and performance, by optimally demodulating multiple interfering signals that overlap in time and frequency. This is a major research problem in multipoint-to-point communications. Due to the complexity associated with optimal maximum likelihood detection, many different sub-optimal solutions have been proposed. This focus of this dissertation is the application of neural networks for MUD, in a direct sequence CDMA (DS-CDMA) system. Specifically, it explores how the Hopfield recurrent neural network (RNN) can be employed to give yet another suboptimal solution to the optimization problem of MUD. There is great scope for neural networks in fields encompassing communications. This is primarily attributed to their non-linearity, adaptivity and key function as data classifiers. In the context of optimum multiuser detection, neural networks have been successfully employed to solve similar combinatorial optimization problems. The concepts of CDMA and MUD are discussed. The use of a vector-valued transmission model for DS-CDMA is illustrated, and common linear sub-optimal MUD schemes, as well as the maximum likelihood criterion, are reviewed. The performance of these sub-optimal MUD schemes is demonstrated. The Hopfield neural network (HNN) for combinatorial optimization is discussed. Basic concepts and techniques related to the field of statistical mechanics are introduced and it is shown how they may be employed to analyze neural classification. Stochastic techniques are considered in the context of improving the performance of the HNN. A neural-based receiver, which employs a stochastic HNN and a simulated annealing technique, is proposed. Its performance is analyzed in a communication channel that is affected by additive white Gaussian noise (AWGN) by way of simulation. The performance of the proposed scheme is compared to that of the single-user matched filter, linear decorrelating and minimum mean-square error detectors, as well as the classical HNN and the stochastic Hopfield network (SHN) detectors. Concluding, the feasibility of neural networks (in this case the HNN) for MUD in a DS-CDMA system is explored by quantifying the relative performance of the proposed model using simulation results and in view of implementation issues