In this thesis, we present a space-time coded system which achieves high through- put and good performance with low processing delay using low-complexity detection and decoding. Initially, Hamming codes are used in a simple interleaved bit-mapped coded modulation structure (BMCM). This is concatenated with Alamouti's or- thogonal space-time block codes. The good performance achieved by this system indicates that higher throughput is possible while maintaining performance. An analytical bound for the performance of this system is presented. We also develop a class of low density parity check codes which allows flexible "throughput versus performance" tradeoffs. We then focus on a Rate 2 quasi-orthogonal space-time block code structure which enables us to achieve an overall throughput of 5.6 bits/symbol period with good performance and relatively simple decoding using iterative parallel interference cancellation. We show that this can be achieved through the use of a bit-mapped coded modulation structure using parallel short low density parity check codes. The absence of interleavers here reduces processing delay significantly. The proposed system is shown to perform well on flat Rayleigh fading channels with a wide range of normalized fade rates, and to be robust to channel estimation errors. A comparison with bit-interleaved coded modulation is also provided (BICM).

Yes / The paper presents a technique to enhance the isolation between adjacent radiating elements which is common in densely packed antenna arrays. Such antennas provide frequency beam-scanning capability needed in Multiple-Input Multiple-Output (MIMO) systems and Synthetic Aperture Radars (SARs). The method proposed here uses a metamaterial decoupling slab (MTMDS), which is located between radiating elements, to suppress mutual-coupling between the elements that would otherwise degrade the antenna efficiency and performance in both the transmit and receive mode. The proposed MTM-DS consists of mirror imaged Eshaped slits engraved on a microstrip patch with inductive stub. Measured results confirm over 9–11 GHz with no MTM-DS the average isolation (S12) is -27 dB; however, with MTM-DS the average isolation improves to -38 dB. With this technique the separation between the radiating element can be reduced to 0.66λo, where λ0 is free space wavelength at 10 GHz. In addition, with this technique there is 15% improvement in operating bandwidth. At frequencies of high impedance match of 9.95 GHz and 10.63 GHz the gain is 4.52 dBi and 5.40 dBi, respectively. Furthermore, the technique eliminates poor front-to-back ratio encountered in other decoupling methods. MTM-DS is also relatively simple to implement. Assuming adequate space is available between adjacent radiators the MTM-DS can be fixed retrospectively on existing antenna arrays, which makes the proposed method versatile. / Partially supported by innovation programme under grant agreement H2020-MSCA-ITN-2016 SECRET- 722424 and the financial support from the UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/E022936/1.

<p>The Multiple-input and Multiple-output (MIMO) channel model is very useful for the presentation of a wide range of wireless communication systems. This thesis addresses the joint design of a precoder and a receiver for a MIMO channel model, in a scenario in which perfect channel state information (CSI) is available at both ends. We develop a novel framework for the transmitting-receiving procedure. Under the proposed framework, the receiver decomposes the channel matrix by using a block QR decomposition, where Q is a unitary matrix and R is a block upper triangular matrix. The optimal maximum likelihood (ML) detection process is employed within each diagonal block of R. Then, the detected block of symbols is substituted and subtracted sequentially according to the block QR decomposition based successive cancellation. On the transmitting end, the expression of probability of error based on ML detection is chosen as the design criterion to formulate the precoder design problem. This thesis presents a design of MIMO transceivers in the particular case of having 4 transmitting and 4 receiving antennas with full CSI knowledge on both sides. In addition, a closed-form expression for the optimal precoder matrix is obtained for channels satisfying certain conditions. For other channels not satisfying the specific condition, a numerical method is applied to obtain the optimal precoder matrix.</p> / Master of Applied Science (MASc)

In this thesis, our focus is on low-complexity, high-performance detection algorithms for multi-antenna communication receivers. A key contribution in this thesis is the demonstration that efficient algorithms from metaheuristics and machine learning can be gainfully adapted for signal detection in multi- antenna communication receivers. We first investigate a popular metaheuristic known as the reactive tabu search (RTS), a combinatorial optimization technique, to decode the transmitted signals in large-dimensional communication systems. A basic version of the RTS algorithm is shown to achieve near-optimal performance for 4-QAM in large dimensions. We then propose a method to obtain a lower bound on the BER performance of the optimal detector. This lower bound is tight at moderate to high SNRs and is useful in situations where the performance of optimal detector is needed for comparison, but cannot be obtained due to very high computational complexity. To improve the performance of the basic RTS algorithm for higher-order modulations, we propose variants of the basic RTS algorithm using layering and multiple explorations. These variants are shown to achieve near-optimal performance in higher-order QAM as well. Next, we propose a new receiver called linear regression of minimum mean square error (MMSE) residual receiver (referred to as LRR receiver). The proposed LRR receiver improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel) to find the linear regression parameters. The LRR receiver is suitable for applications where the channel remains constant for a long period (slow-fading channels) and performs well. Finally, we propose a receiver that uses a committee of linear receivers, whose parameters are estimated from training data using a variant of the AdaBoost algorithm, a celebrated supervised classification algorithm in ma- chine learning. We call our receiver boosted MMSE (B-MMSE) receiver. We demonstrate that the performance and complexity of the proposed B-MMSE receiver are quite attractive for multi-antenna communication receivers.

One of the most popular ways to exploit the advantages of a multiple-input multiple-output (MIMO) system is using space time block coding. A space time block code (STBC) is a finite set of complex matrices whose entries consist of the information symbols to be transmitted. A linear STBC is one in which the information symbols are linearly combined to form a two-dimensional code matrix. A well known method of maximum-likelihood (ML) decoding of such STBCs is using the sphere decoder (SD). In this thesis, new constructions of STBCs with low sphere decoding complexity are presented and various ways of characterizing and reducing the sphere decoding complexity of an STBC are addressed. The construction of low sphere decoding complexity STBCs is tackled using irreducible matrix representations of Clifford algebras, cyclic division algebras and crossed-product algebras. The complexity reduction algorithms for the STBCs constructed are explored using tree based search algorithms. Considering an STBC as a vector space over the set of weight matrices, the problem of characterizing the sphere decoding complexity is addressed using quadratic form representations. The main results are as follows. A sub-class of fast decodable STBCs known as Block Orthogonal STBCs (BOSTBCs) are explored. A set of sufficient conditions to obtain BOSTBCs are explained. How the block orthogonal structure of these codes can be exploited to reduce the SD complexity of the STBC is then explained using a depth first tree search algorithm. Bounds on the SD complexity reduction and its relationship with the block orthogonal structure are then addressed. A set of constructions to obtain BOSTBCs are presented next using Clifford unitary weight designs (CUWDs), Coordinate-interleaved orthogonal designs (CIODs), cyclic division algebras and crossed product algebras which show that a lot of codes existing in literature exhibit the block orthogonal property. Next, the dependency of the ordering of information symbols on the SD complexity is discussed following which a quadratic form representation known as the Hurwitz-Radon quadratic form (HRQF) of an STBC is presented which is solely dependent on the weight matrices of the STBC and their ordering. It is then shown that the SD complexity is only a function of the weight matrices defining the code and their ordering, and not of the channel realization (even though the equivalent channel when SD is used depends on the channel realization). It is also shown that the SD complexity is completely captured into a single matrix obtained from the HRQF. Also, for a given set of weight matrices, an algorithm to obtain a best ordering of them leading to the least SD complexity is presented using the HRQF matrix.