This thesis develops a novel technique for low-complexity MIMO detection known as Constellation Shift Binary Classification (CSBC). The proposed method utilizes the constellation structure to deduce a constellation shift that is used to reduce the problem of detecting the symbol into binary classification. The proposed method is proven to outperform other common techniques such as ZF and LMMSE. The proposed CSBC is a novel MIMO detection technique since it utilizes the constellation structure together with a binary classifier that is based on neural networks.
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.
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.
MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). In MIMO-OFDM Wireless Communications with MATLAB®, the authors provide a comprehensive introduction to the theory and practice of wireless channel modeling, OFDM, and MIMO, using MATLAB® programs to simulate the various techniques on MIMO-OFDM systems. One of the only books in the area dedicated to explaining simulation aspects Covers implementation to help cement the key concepts Uses materials that have been classroom-tested in numerous universities Provides the analytic solutions and practical examples with downloadable MATLAB® codes Simulation examples based on actual industry and research projects Presentation slides with key equations and figures for instructor use MIMO-OFDM Wireless Communications with MATLAB® is a key text for graduate students in wireless communications. Professionals and technicians in wireless communication fields, graduate students in signal processing, as well as senior undergraduates majoring in wireless communications will find this book a practical introduction to the MIMO-OFDM techniques. Instructor materials and MATLAB® code examples available for download at www.wiley.com/go/chomimo
This textbook takes a unified view of the fundamentals of wireless communication and explains cutting-edge concepts in a simple and intuitive way. An abundant supply of exercises make it ideal for graduate courses in electrical and computer engineering and it will also be of great interest to practising engineers.
This exclusive coverage of the opportunities, technological challenges, solutions, and state of the art of large MIMO systems provides an in-depth discussion of algorithms for large MIMO signal processing, suited for large MIMO signal detection, precoding and LDPC code designs. An ideal resource for researchers, designers, developers and practitioners in wireless communications.
