Quasi-Optimum Detection for a Wide Class of Digital Signals with Strong Nonlinear Distortion Effects

Most of the signals widely employed in wireless communications can have significant envelope fluctuations that make them very prone to nonlinear (NL) effects, leading to significant performance degradation when conventional receivers (designed for ideal linear conditions) are utilized. However, if optimum maximum likelihood (ML) receivers are employed, NL effects do not necessarily lead to performance degradation, and can actually outperform the corresponding linear systems. This paper presents a general framework for studying the impact of NL effects on a wide class of block transmission techniques with blockwise pre-processing where the transmitted signals have significant envelope fluctuations. This class includes many of the widely employed transmission techniques like Orthogonal Frequency Division Multiplexing (OFDM), Multiple-Input Multiple-Output (MIMO), Single Carier-Frequency Domain Equalization (SC-FDE) and Code Division Multiple Access (CDMA). Our approach provides accurate bounds on the achievable performance of optimum receivers, and enables the design of iterative receivers able to approach that optimum performance with complexity much lower than the corresponding optimum ML receivers.