Adaptive equalizer based on a power-of-two-quantized-LMF algorithm

High speed and reliable data transmission over a variety of communication channels, including wireless and mobile radio channels, has been rendered possible through the use of adaptive equalization. In practice, adaptive equalizers rely heavily on the use of the least-mean square (LMS) algorithm which performs sub-optimally in the real world that is largely dominated by non-Gaussian interference signals. This paper proposes a new adaptive equalizer which relies on the judicious combination of the least-mean fourth (LMF) algorithm, which ensures a better performance in a non-Gaussian environment, and the power-of-two quantizer (PTQ) which reduces the high computational load brought about by the LMF and hence renders the proposed low-complexity equalizer capable of tracking fast-changing channels. This paper also presents a performance analysis of the proposed adaptive equalizer, based on a new linear approximation of the PTQ. Finally, the extensive simulation carried out here using the quantized LMF corroborates very well the theoretical predictions provided by the analysis of the linearized proposed algorithm.