Low Complexity MIMO Detection


Book Description

Low Complexity MIMO Detection introduces the principle of MIMO systems and signal detection via MIMO channels. This book systematically introduces the symbol detection in MIMO systems. Includes the fundamental knowledge of MIMO detection and recent research outcomes for low complexity MIMO detection.










Algorithms and VLSI Implementations of MIMO Detection


Book Description

This book provides a detailed overview of detection algorithms for multiple-input multiple-output (MIMO) communications systems focusing on their hardware realisation. The book begins by analysing the maximum likelihood detector, which provides the optimal bit error rate performance in an uncoded communications system. However, the maximum likelihood detector experiences a high complexity that scales exponentially with the number of antennas, which makes it impractical for real-time communications systems. The authors proceed to discuss lower-complexity detection algorithms such as zero-forcing, sphere decoding, and the K-best algorithm, with the aid of detailed algorithmic analysis and several MATLAB code examples. Furthermore, different design examples of MIMO detection algorithms and their hardware implementation results are presented and discussed. Finally, an ASIC design flow for implementing MIMO detection algorithms in hardware is provided, including the system simulation and modelling steps and register transfer level modelling using hardware description languages. Provides an overview of MIMO detection algorithms and discusses their corresponding hardware implementations in detail; Highlights architectural considerations of MIMO detectors in achieving low power consumption and high throughput; Discusses design tradeoffs that will guide readers’ efforts when implementing MIMO algorithms in hardware; Describes a broad range of implementations of different MIMO detectors, enabling readers to make informed design decisions based on their application requirements.




Massive MIMO Detection Algorithm and VLSI Architecture


Book Description

This book introduces readers to a reconfigurable chip architecture for future wireless communication systems, such as 5G and beyond. The proposed architecture perfectly meets the demands for future mobile communication solutions to support different standards, algorithms, and antenna sizes, and to accommodate the evolution of standards and algorithms. It employs massive MIMO detection algorithms, which combine the advantages of low complexity and high parallelism, and can fully meet the requirements for detection accuracy. Further, the architecture is implemented using ASIC, which offers high energy efficiency, high area efficiency and low detection error. After introducing massive MIMO detection algorithms and circuit architectures, the book describes the ASIC implementation for verifying the massive MIMO detection. In turn, it provides detailed information on the proposed reconfigurable architecture: the data path and configuration path for massive MIMO detection algorithms, including the processing unit, interconnections, storage mechanism, configuration information format, and configuration method.







Low Complexity MIMO Receivers


Book Description

Multiple-input multiple-output (MIMO) systems can increase the spectral efficiency in wireless communications. However, the interference becomes the major drawback that leads to high computational complexity at both transmitter and receiver. In particular, the complexity of MIMO receivers can be prohibitively high. As an efficient mathematical tool to devise low complexity approaches that mitigate the interference in MIMO systems, lattice reduction (LR) has been widely studied and employed over the last decade. The co-authors of this book are world's leading experts on MIMO receivers, and here they share the key findings of their research over years. They detail a range of key techniques for receiver design as multiple transmitted and received signals are available. The authors first introduce the principle of signal detection and the LR in mathematical aspects. They then move on to discuss the use of LR in low complexity MIMO receiver design with respect to different aspects, including uncoded MIMO detection, MIMO iterative receivers, receivers in multiuser scenarios, and multicell MIMO systems.




Low Complexity Detection Techniques for MIMO and Cooperative Networks


Book Description

This thesis investigates detection technologies for multiple-input multiple-output (MIMO) systems and cooperative communications. The exploitation of detection methods and relay strategies to achieve near-optimal performance (measured by symbol error rate or minimum mean squared error) and reductions of the running time of detection methods are the main focus of this thesis. A signal-to-noise ratio (SNR)-dependent radius control sphere detector (SD) algorithm, a general framework of statistical pruning SD, and an improved K-best SD are proposed. These SD algorithms reduce the detection running time in terms of the average number of visited nodes, with negligible performance loss compared with that of optimal maximum likelihood (ML) detection. In order to optimize the MIMO relay performance, an estimate-and-forward (EF) relay strategy is also developed. The emerging trend towards large MIMO and cooperative communication systems makes the development of low running time strategies with near-optimal performance more important. Thus, an EF list generated by SD is also proposed to reduce the number of computational operations for the EF scheme in large MIMO relay networks; this method is called list EF. Overall, the research findings should help to reduce the running time and improve the reliability of detection algorithms, to achieve a desirable trade-off between running time and performance, and to provide efficiently-implementable MIMO and cooperative detection algorithms.




Lattice Reduction for MIMO Detection


Book Description

The objective of the dissertation research is to understand the complex interaction between the algorithm and hardware aspects of symbol detection that is nhanced by lattice reduction (LR) preprocessing for wireless MIMO communication systems. The motivation for this work stems from the need to improve the bit-error-ate performance of conventional, low-complexity detectors while simultaneously exhibiting considerably reduced complexity when compared to the optimal method, aximum likelihood detection. Specifically, we first develop an understanding of the complex Lenstra-Lenstra-Lov©3¡sz (CLLL) LR algorithm from a hardware perspective. his understanding leads to both algorithm modifications that reduce the required complexity and hardware architectures that are specifically optimized for the CLLL lgorithm. Finally, we integrate this knowledge with an understanding of LR-aided MIMO symbol detection in a highly-correlated wireless environment, resulting in a joint R/symbol detection algorithm that maps seamlessly to hardware. Hence, this dissertation forms the foundation for the adoption of lattice reduction algorithms in ractical, high-throughput wireless MIMO communications systems.