Simplified Robust Adaptive Detection and Beamforming for Wireless Communications
Chapter 1 – Introduction Chapter 2 - Wireless Systems Models Chapter 3 - Adaptive Detection Algorithms Chapter 4 - Robust RLS Adaptive Algorithms Chapter 5 - Quadratically Constrained Robust Detection Chapter 6 - Robust Constant Modulus Algorithms Chapter 7 - Robust Adaptive Beamforming Chapter 8 - Minimum BER Adaptive Detection and Beamforming
Ayman Elnashar, PhD, has 20+ years of experience in the telecoms industry, including 2G/3G/LTE/WiFi/IoT/5G/Wireless Networks. He was part of three major start-up telecom operators in the MENA region (Orange/Egypt, Mobily/KSA, and du/UAE). Currently, he is Head of Core and Cloud planning with the Emirates Integrated Telecommunications Co. "du", UAE. He is the founder of the Terminal Innovation Lab and UAE 5G Innovation Gate (U5GIG). Prior to this, he was Sr. Director – Wireless Networks, Terminals and IoT, where he managed and directed the evolution, evaluation, and introduction of du wireless networks, terminals and IoT, including LTE/LTE-A, HSPA+, WiFi, NB-IoT, and is currently working towards deploying 5G network in the UAE.
Provides a Systematic Overview of Robust Adaptive Detection and Beamforming Techniques Supported with MATLAB® Scripts, Practical Examples, and Simulation Results for Major Wireless Communications Systems This book presents alternative and simplified approaches for the robust adaptive detection and beamforming in wireless communications. It adopts several systems models including DS/CDMA, OFDM/MIMO with antenna array, and general antenna arrays beamforming model. The text presents and analyzes recently developed detection and beamforming algorithms with an emphasis on robustness. In addition, simplified and efficient robust adaptive detection and beamforming techniques are presented and compared with existing techniques. Practical examples based on the above systems models are provided to exemplify the developed detectors and beamforming algorithms. Moreover, the developed techniques are implemented using MATLAB®—and the relevant MATLAB® scripts are provided to help readers develop and analyze the presented algorithms. Simplified Robust Adaptive Detection and Beamforming for Wireless Communications starts by introducing readers to adaptive signal processing and robust adaptive detection. It then goes on to cover Wireless Systems Models. The robust adaptive detectors and beamformers are implemented using the well-known algorithms, including: LMS, RLS, IQRD-RLS, RSD, BSCMA, CG, and SD. The robust detection and beamforming are derived based on the existing detectors/beamformers including MOE, PLIC, LCCMA, LCMV, MVDR, BSCMA, and MBER. The adopted cost functions include MSE, BER, CM, MV and SINR/SNR. Introduces and addresses robustness in adaptive detection and beamforming Offers simplified approaches to add robustness to adaptive signal processing algorithms while maintaining optimality with less computational complexity Presented algorithms are illustrated with practical examples and simulation results for major wireless communications systems including DS/CDMA, OFDM/MIMO, and smart antenna systems Offers MATLAB® scripts for further analysis and development Simplified Robust Adaptive Detection and Beamforming for Wireless Communications will appeal to R&D engineers, researchers, wireless chipset development companies, and graduate students that are interested in signal processing and its advanced techniques.
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