Applications of Independent Component Analysis in Wireless Communication Systems

Abstract

Independent component analysis (ICA) is a signal processing technique used for separating statistically independent and non-Gaussian mixed signals. It is widely used in different areas e.g., wireless communication, speech and biomedical signal processing, vibration analysis, and machinery fault diagnosis. In wireless communication systems, ICA has been used in multiple input multiple output systems, wireless sensor networks, cognitive radio networks, code division multiple access , and orthogonal frequency division multiplexing. The applications of ICA in wireless communication include the suppression of inter symbol interference, cancellation of inter channel interference, direction of arrival estimation, automatic classification of modulation, and spectrum sensing etc. This paper provides a comprehensive survey on the applications of ICA in various wireless communication systems along with the survey of mixing models used in the theory of ICA. The techniques for estimating the number of signals in received mixed signals are also studied. We also surveyed the ICA applications in time varying mixing scenario. The challenges and limitations of ICA regarding wireless communication systems are also presented. This paper also outlines future research directions related to the field of applications of ICA in wireless communication systems.