Blind Source Separation of Optical Wireless Communications in Noisy Environments

TL;DR

This paper presents an improved low-complexity blind source separation algorithm for optical wireless communications, demonstrating its effectiveness across various noisy environments and expanding its practical applicability.

Contribution

It introduces a simplified blind separation algorithm with a tunable parameter and extends its use to visible light communication signals in noisy settings.

Findings

Algorithm's separation performance is significantly affected by the moving average length.

The extended algorithm effectively separates signals in different noise environments.

Experimental results validate the algorithm's applicability to optical wireless communications.

Abstract

Blind source separation is a research hotspot in the field of signal processing because it aims to separate unknown source signals from observed mixtures through an unknown transmission channel. A low computational complexity instantaneous linear mixture signals blind separation algorithm was introduced and improved. There is only one variable parameter named the length of moving average in the algorithm, which has a significant impact on the separation effect. This paper gives some suggestions on the reasonable value through experiments. The algorithm is extended to the separation of visible light communication signals in different noise environments, and has achieved certain results, which further expands the applicability of the algorithm.