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

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

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..

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

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

Hybrid Dy-NFIS & RLS equalization for ZCC code in optical-CDMA over multi-mode optical fiber

For long haul coherent optical fiber communication systems, it is significant to precisely monitor the quality of transmission links and optical signals. The channel capacity beyond Shannon limit of Single-mode optical fiber (SMOF) is achieved with the help of Multi-mode optical fiber (MMOF), where the signal is multiplexed in different spatial modes. To increase single-mode transmission capacity and to avoid a foreseen “capacity crunch”, researchers have been motivated to employ MMOF as an alternative. Furthermore, different multiplexing techniques could be applied in MMOF to improve the communication system. One of these techniques is the Optical Code Division Multiple Access (Optical-CDMA), which simplifies and decentralizes network controls to improve spectral efficiency and information security increasing flexibility in bandwidth granularity. This technique also allows synchronous and simultaneous transmission medium to be shared by many users. However, during the propagation of the data over the MMOF based on Optical-CDMA, an inevitable encountered issue is pulse dispersion, nonlinearity and MAI due to mode coupling. Moreover, pulse dispersion, nonlinearity and MAI are significant aspects for the evaluation of the performance of high-speed MMOF communication systems based on Optical-CDMA. This work suggests a hybrid algorithm based on nonlinear algorithm (Dynamic evolving neural fuzzy inference (Dy-NFIS)) and linear algorithm (Recursive least squares (RLS)) equalization for ZCC code in Optical-CDMA over MMOF. Root mean squared error (RMSE), mean squared error (MSE) and Structural Similarity index (SSIM) are used to measure performance results

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

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School