A novel complexity reduction using similarity property in ML-ZF detection for MIMO systems

Abstract

In this letter, we propose a method that combines breadth first tree search Maximum Likelihood (ML) and Zero Forcing (ZF) detection for spatial multiplexing Multiple Input Multiple Output (MIMO systems utilizing the similarity property of the Quadrature amplitude modulation (QAM) to detect the symbol. The proposed method shows substantial reduction in complexity, in terms of both reducing the number of nodes and number of operation to be performed at each node of the tree. The simulation results show that this approach achieves 48% of reduction in the computational complexity compared to breadth first ML with reduced nodes for a 2×2 systems and 75% for the 4×4 systems without any degradation in the performance.