Simplified Robust Adaptive Detection and Beamforming for Wireless Communications

1Introduction

1.1 Motivation

This book presents alternative and simplified approaches for the robust adaptive detection and beamforming in wireless communications. The book adopts several system models, including:

• DS/CDMA, with and without antenna array
• MIMO‐OFDM with antenna array
• general smart antenna array model.

Recently developed detection and beamforming algorithms are presented and analyzed with an emphasis on robustness. In addition, simplified and efficient robust adaptive detection and beamforming techniques are developed and compared with existing techniques. The robust detectors and beamformers are implemented using well‐known algorithms including, but not limited to:

• least‐mean‐square
• recursive least‐squares (RLS)
• inverse QR decomposition RLS (IQRD‐RLS)
• fast recursive steepest descent (RSD)
• block‐Shanno constant modulus (BSCMA)
• conjugate gradient (CG)
• steepest descent (SD).

The robust detection and beamforming methods are derived from existing detectors/beamformers including, but not limited to:

• the robust minimum output energy (MOE) detector
• partition linear interference canceller (PLIC) detector
• linearly constrained constant modulus (CM) algorithm (LCCMA),
• linearly constrained minimum variance (LCMV) beamforming with single constraint,
• minimum variance distortionless response (MVDR) beamformer with multiple constraint
• block Shanno constant modulus algorithm (BSCMA) based detector/beamformer
• adaptive minimum bit error rate (BER) based detectors.

The adopted cost functions ...