Ray tracing based on geometric optics can be utilized for generating propagation models for arbitrary and complex environments. These methods can be employed to determine important wireless channel characteristics such as path gain and the channel impulse response which in turn can be used to deduce channel capacity. In this thesis, a fully vectorial 3-D ray-tracer is developed. The simulator is applied to study novel wireless systems such as ultra-wideband pulse propagation in complex railway tunnels and MIMO systems employing closely spaced low mutual coupling meta-material antennas. The computational complexity of the ray-tracing algorithm is reduced using optimizations and via the development of a novel hybrid method that combines the efficiency and accuracy of waveguide models with the flexibility of a ray-tracer. The resulting simulator is validated against measured results and demonstrated to show good agreement. Convergence of the solution using the ray-tracing method is also discussed.

In wireless communications, the use of multiple antennas at both the transmitter and the receiver is a key technology to enable high data rate transmission without additional bandwidth or transmit power. Multiple-input multiple-output (MIMO) schemes are widely used in many wireless standards, allowing higher throughput using spatial multiplexing techniques. MIMO soft detection poses significant challenges to the MIMO receiver design as the detection complexity increases exponentially with the number of antennas. As the next generation wireless system is pushing for multi-Gbps data rate, there is a great need for high-throughput low-complexity soft-output MIMO detector. The brute-force implementation of the optimal MIMO detection algorithm would consume enormous power and is not feasible for the current technology. We propose a reduced-complexity soft-output MIMO detector architecture based on a trellis-search method. We convert the MIMO detection problem into a shortest path problem. We introduce a path reduction and a path extension algorithm to reduce the search complexity while still maintaining sufficient soft information values for the detection. We avoid the missing counter-hypothesis problem by keeping multiple paths during the trellis search process. The proposed trellis-search algorithm is a data-parallel algorithm and is very suitable for high speed VLSI implementation. Compared with the conventional tree-search based detectors, the proposed trellis-based detector has a significant improvement in terms of detection throughput and area efficiency. The proposed MIMO detector has great potential to be applied for the next generation Gbps wireless systems by achieving very high throughput and good error performance. The soft information generated by the MIMO detector will be processed by a channel decoder, e.g. a low-density parity-check (LDPC) decoder or a Turbo decoder, to recover the original information bits. Channel decoder is another very computational-intensive block in a MIMO receiver SoC (system-on-chip). We will present high-performance LDPC decoder architectures and Turbo decoder architectures to achieve 1+ Gbps data rate. Further, a configurable decoder architecture that can be dynamically reconfigured to support both LDPC codes and Turbo codes is developed to support multiple 3G/4G wireless standards. We will present ASIC and FPGA implementation results of various MIMO detectors, LDPC decoders, and Turbo decoders. We will discuss in details the computational complexity and the throughput performance of these detectors and decoders.

Empowered by linear precoding and decoding, a spatially multiplexed multiple-input multiple-output (MIMO) system becomes a convenient framework to offer high data rate, diversity and interference management. While most of the current precoding/decoding designs have assumed perfect channel state information (CSI) at the receiver, and sometimes even at the transmitter, in this thesis we design the precoder and decoder with imperfect CSI at both the transmit and the receive sides, and investigate the joint impact of channel estimation errors and channel correlation on system structure and performance. The mean-square error (MSE) related performance metrics are used as the design criteria. We begin with the minimum total MSE precoding/decoding design for a single-user MIMO system assuming imperfect CSI at both ends. Here the CSI includes the channel estimate and channel correlation information. The structures of the optimum precoder and decoder are determined. Compared to the perfect CSI case, linear filters are added to the transceiver structure to improve system robustness against imperfect CSI. The effects of channel estimation error and channel correlation are quantified by simulations. With imperfect CSI at both ends, the exact capacity expression for a single-user MIMO channel is difficult to obtain. Instead, a tight capacity lower-bound is used for system design. The optimum structure of the transmit covariance matrix for the lower-bound has not been found in the existing literature. By transforming the transmitter design into a joint precoding/decoding design problem, we derive the expression of the optimum transmit covariance matrix. The close relationship between the maximum mutual information design and the minimum total MSE design is also discovered assuming imperfect CSI. For robust multiuser MIMO communications, minimum average sum MSE transceiver (precoder-decoder pairs) design problems are formulated for both the uplink and the downlink, assuming imperfect channel estimation and channel correlation at the base station (BS). We propose improved iterative algorithms based on the associated Karush-Kuhn-Tucker (KKT) conditions. Under the assumption of imperfect CSI, an uplink--downlink duality in average sum MSE is proved. As an alternative for the uplink optimization, a sequential semidefinite programming (SDP) method is proposed. Simulation results are provided to corroborate the analysis. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-07-25 10:53:45.175

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Collaborative beamforming is a powerful technique to increase communication energy efficiency and range in an energy-constrained network. To achieve high performance, collaborative beamforming requires accurate knowledge of channel state information (CSI) at the transmitters (collaborative nodes). In practice, however, such exact knowledge of CSI is not available. A robust transmitter design based on partial CSI is required to mitigate the effects of CSI mismatches. / This thesis focuses on the design and evaluation of a beamforming scheme that is robust to CSI mismatches for collaborative multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) wireless systems. Using a max-min robust design approach, the robust beamformer is designed to maximize the minimum (worst-case) received signal-to-noise ratio (SNR) within a predefined uncertainty region at each OFDM subcarrier. In addition, several subcarrier power allocation strategies are investigated to further improve the robustness of collaborative systems. Numerical simulation results show that the robust beamformer offers improved performance over the nonrobust beamformers and the use of power allocation strategies among subcarriers further improves the system performance.

Telecommunications in the current information age is increasingly relying on the wireless link. This is because wireless communication has made possible a variety of services ranging from voice to data and now to multimedia. Consequently, demand for new wireless capacity is growing rapidly at a very alarming rate. In a bid to cope with challenges of increasing demand for higher data rate, better quality of service, and higher network capacity, there is a migration from Single Input Single Output (SISO) antenna technology to a more promising Multiple Input Multiple Output (MIMO) antenna technology. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) technique has emerged as a very popular multi-carrier modulation technique to combat the problems associated with physical properties of the wireless channels such as multipath fading, dispersion, and interference. The combination of MIMO technology with OFDM techniques, known as MIMO-OFDM Systems, is considered as a promising solution to enhance the data rate of future broadband wireless communication Systems. This thesis addresses a major area of challenge to both SISO-OFDM and MIMO-OFDM Systems; estimation of accurate channel state information (CSI) in order to make possible coherent detection of the transmitted signal at the receiver end of the system. Hence, the first novel contribution of this thesis is the development of a low complexity adaptive algorithm that is robust against both slow and fast fading channel scenarios, in comparison with other algorithms employed in literature, to implement soft iterative channel estimator for turbo equalizer-based receiver for single antenna communication Systems. Subsequently, a Fast Data Projection Method (FDPM) subspace tracking algorithm is adapted to derive Channel Impulse Response Estimator for implementation of Decision Directed Channel Estimation (DDCE) for Single Input Single Output - Orthogonal Frequency Division Multiplexing (SISO-OFDM) Systems. This is implemented in the context of a more realistic Fractionally Spaced-Channel Impulse Response (FS-CIR) channel model, as against the channel characterized by a Sample Spaced-Channel Impulse Response (SS)-CIR widely assumed by other authors. In addition, a fast convergence Variable Step Size Normalized Least Mean Square (VSSNLMS)-based predictor, with low computational complexity in comparison with others in literatures, is derived for the implementation of the CIR predictor module of the DDCE scheme. A novel iterative receiver structure for the FDPM-based Decision Directed Channel Estimation scheme is also designed for SISO-OFDM Systems. The iterative idea is based on Turbo iterative principle. It is shown that improvement in the performance can be achieved with the iterative DDCE scheme for OFDM system in comparison with the non iterative scheme. Lastly, an iterative receiver structure for FDPM-based DDCE scheme earlier designed for SISO OFDM is extended to MIMO-OFDM Systems. In addition, Variable Step Size Normalized Least Mean Square (VSSNLMS)-based channel transfer function estimator is derived in the context of MIMO Channel for the implementation of the CTF estimator module of the iterative Decision Directed Channel Estimation scheme for MIMO-OFDM Systems in place of linear minimum mean square error (MMSE) criterion. The VSSNLMS-based channel transfer function estimator is found to show improved MSE performance of about -4 MSE (dB) at SNR of 5dB in comparison with linear MMSE-based channel transfer function estimator. / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2010.

Multiple-input multiple-output (MIMO) systems have been extensively studied in the past decade. The attractiveness of MIMO systems is due to the fact that they drastically reduce the deleterious e ects of multipath fading leading to high system capacity and low error rates. In situations where wireless devices are restrained by their size and hardware complexity, such as mobile phones, transmit diversity is not achievable. A new paradigm called cooperative communication is a viable solution. In a cooperative scenario, a single-antenna device is assisted by another single-antenna device to relay its message to the destination or base station. This creates a virtual multiple-input multiple-output (MIMO) system. There exist two cooperative strategies: amplify-and-forward (AF) and decode-and-forward (DF). In the former, the relay ampli es the noisy signal received from the source before forwarding it to the destination. No form of demodulation is required. In the latter, the relay rst decodes the source signal before transmitting an estimate to the destination. In this work, focus is on the DF method. A drawback of an uncoded DF cooperative strategy is error propagation at the relay. To avoid error propagation in DF, various relay selection schemes can be used. Coded cooperation can also be used to avoid error propagation at the relay. Various error correcting codes such as convolutional codes or turbo codes can be used in a cooperative scenario. The rst part of this work studies a variation of the turbo codes in cooperative diversity, that further reduces error propagation at the relay, hence lowering the end-to-end error rate. The union bounds on the bit-error rate (BER) of the proposed scheme are derived using the pairwise error probability via the transfer bounds and limit-before-average techniques. In addition, the outage analysis of the proposed scheme is presented. Simulation results of the bit error and outage probabilities are presented to corroborate the analytical work. In the case of outage probability, the computer simulation results are in good agreement with the the analytical framework presented in this chapter. Recently, most studies have focused on cross-layer design of cooperative diversity at the physical layer and truncated automatic-repeat request (ARQ) at the data-link layer using the system throughput as the performance metric. Various throughput optimization strategies have been investigated. In this work, a cross-relay selection approach that maximizes the system throughput is presented. The cooperative network is comprised of a set of relays and the reliable relay(s) that maximize the throughput at the data-link layer are selected to assist the source. It can be shown through simulation that this novel scheme outperforms from a throughput point of view, a system throughput where the all the reliable relays always participate in forwarding the source packet. A power optimization of the best relay uncoded DF cooperative diversity is investigated. This optimization aims at maximizing the system throughput. Because of the non-concavity and non-convexity of the throughput expression, it is intractable to derive a closed-form expression of the optimal power through the system throughput. However, this can be done via the symbol-error rate (SER) optimization, since it is shown that minimizing the SER of the cooperative system is equivalent to maximizing the system throughput. The SER of the retransmission scheme at high signal-to-noise ratio (SNR) was obtained and it was noted that the derived SER is in perfect agreement with the simulated SER at high SNR. Moreover, the optimal power allocation obtained under a general optimization problem, yields a throughput performance that is superior to non-optimized power values from moderate to high SNRs. The last part of the work considers the throughput maximization of the multi-relay adaptive DF over independent and non-identically distributed (i.n.i.d.) Rayleigh fading channels, that integrates ARQ at the link layer. The aim of this chapter is to maximize the system throughput via power optimization and it is shown that this can be done by minimizing the SER of the retransmission. Firstly, the closed-form expressions for the exact SER of the multi-relay adaptive DF are derived as well as their corresponding asymptotic bounds. Results showed that the optimal power distribution yields maximum throughput. Furthermore, the power allocated at a relay is greatly dependent of its location relative to the source and destination. / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2013.

Future wireless communication systems promise to offer a variety of multimedia services which require reliable transmission at high data rates over wireless links. Multiple input multiple output (MIMO) systems have received a great deal of attention because they provide very high data rates for such links. Theoretical studies have shown that the quality provided by MIMO systems can be increased by using space-time codes. Space-time codes combine both space (antenna) and time diversity in the transmitter to increase the efficiency of MIMO system. The three primary approaches, layered spacetime architecture, space-time trellis coding (STTC) and space-time block coding (STBC) represent a way to investigate transmitter-based signal processing for diversity exploitation and interference suppression. The advantages of STBC (i.e. low decoding complexity) and STTC (i.e. TCM encoder structure) can be used to design a high rate space-time trellis coded modulation (HR-STTCM). Most space-time codes designs are based on the assumption of perfect channel state information at the receiver so as to make coherent decoding possible. However, accurate channel estimation requires a long training sequence that lowers spectral efficiency. Part of this dissertation focuses on the performance of HR-STTCM under non-coherent detection where there is imperfect channel state information and also in environment where the channel experiences rapid fading. Prior work on space-time codes with particular reference to STBC systems in multiuser environment has not adequately addressed the performance of the decoupled user signalto-noise ratio. Part of this thesis enumerates from a signal-to-noise ratio point of view the performance of the STBC systems in multiuser environment and also the performance of the HR-STTCM in such environment. The bit/frame error performance of space-time codes in fading channels can be evaluated using different approaches. The Chemoff upper-bound combined with the pair state generalized transfer function bound approach or the modified state transition diagram transfer function bound approach has been widely used in literature. However, although readily detennined, this bound can be too loose over nonnal signal-to-noise ranges of interest. Other approaches, based on the exact calculation of the pairwise error probabilities, are often too cumbersome. A simple exact numerical technique, for calculating, within any desired degree of accuracy, of the pairwise error probability of the HR-STTCM scheme over Rayleigh fading channel is proposed in this dissertation. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.

Multiple-input multiple-output (MIMO) technology has emerged as a popular technique for enhancing the reliability and capacity of wireless communication systems. In this dissertation, we analyze the spatial modulation (SM) MIMO technique and investigate possible extensions to this scheme. To date, there has been no literature reporting on the theoretical performance of M-ary quadrature amplitude modulation (M-QAM) SM with maximum likelihood (ML) based detection. The first objective of this dissertation is to present an asymptotic bound to quantify the average bit error rate (BER) of M-QAM SM with ML detection over independent and identically distributed (i.i.d) Rayleigh flat fading channels. The analytical frameworks are validated by Monte Carlo simulation results, which show the derived bounds to be tight for high signal-to-noise ratio (SNR) values. The ML based SM detector is optimal, since it offers the best detection performance. However, this technique is not practical due to its high computational complexity. The second objective of this dissertation is to introduce a novel SM detection scheme, termed multiple-stage (MS) detection. Performance and complexity comparisons with existing SM detectors show two main benefits of MS detection: near optimal BER performance and up to a 35% reduction in receiver complexity as compared to the ML based detector. Conventional SM schemes are unable to exploit the transmit diversity gains provided by the MIMO channel. The third objective of this dissertation is to propose Alamouti coded spatial modulation (ACSM), a novel SM based scheme with transmit diversity. The ACSM technique combines SM with Alamouti space-time block coding (STBC), thereby improving the diversity aspect and overall system performance of conventional SM. A closed form expression for the average BER of real constellation ACSM over i.i.d Rayleigh flat fading channels is derived and Monte Carlo simulations are used to verify the accuracy of this analytical expression. The BER performance of ACSM is compared to that of SM and Alamouti STBC. Simulation results show that the new scheme outperforms SM and Alamouti STBC by approximately 5.5 dB and 1.5 dB respectively, albeit at the cost of increased receiver complexity. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2010.

Ever increasing demand for higher data rates and better Quality of Service (QoS) for a growing number of users requires new transceiver algorithms and architectures to better exploit the available spectrum and to efficiently counter the impairments of the radio channel. Multiple-Input Multiple-Output (MIMO) communication systems employ multiple antennas at both transmitter and at the receiver to meet the requirements of next-generation wireless systems. It is a promising technology to provide increased data rates while not involving an equivalent increase in the spectral requirements. However, practical implementation of MIMO detectors poses a significant challenge and has been consistently identified as the major bottleneck for realizing the full potential that multiple antenna systems promise. Furthermore, in order to make judicious use of the available bandwidth, the baseband units have to dynamically adapt to different modes (modulation schemes, code rates etc) of operations. Flexibility and high throughput requirements often place conflicting demands on the Very Large Scale Integration (VLSI) system designer. The major focus of this dissertation is to present efficient VLSI architectures for configurable MIMO detectors that can serve as accelerators to enable the realization of next generation wireless devices feasible. Both, hard output and soft output detector architectures are considered.