Comparative survey of signal processing and artificial intelligence based channel equalization techniques and technologies

Abstract

This paper presents an inspection and review of wired and wireless channel equalization techniques and their existing hardware implementations in terms of features, similarities, and differences. The authors begin with the theory behind channel equalization followed by techniques, and the technological realizations for achieving the proper filter in response to variations of the channel. Included in both the techniques and realizations are the rebirth of the use of artificial intelligence as a self-learning filter for the weights to use by the filtering structure of channel equalizers. These equalizers were compared, contrasted, and their key differentiation was identified. It was found that gaps such as complexity and convergence time are potential areas for extending the performance and limits of existing channel equalizers.