Joint Channel and Multi-User Detection Empowered with Machine Learning

The numbers of multimedia applications and their users increase with each passing day. Different multi-carrier systems have been developed along varying techniques space-time coding to address the demand future generation network systems. In this article, a fuzzy logic empowered adaptive backpropagation neural (FLeABPNN) algorithm is proposed for joint channel multi-user detection (CMD). FLeABPNN has two stages. first stage estimates parameters, second performs detection. approach capitalizes on neuro-fuzzy hybrid system that combines competencies both networks. This study analyzes results using based multiple-input multiple-output (MIMO) receiver conventional partial opposite mutant particle swarm optimization (POMPSO), total-OMPSO (TOMPSO), POMPSO (FL-POMPSO), FL-TOMPSO-based MIMO receivers. FLeABPNN-based renders better than other in terms minimum mean square error, bit error rate.