Complexity and Performance Evaluation of Detection Schemes for Spatial Multiplexing MIMO Systems

Abstract

Multiple Input Multiple Output (MIMO) multiplexing is a promising technology that could greatly increase the channel capacity without additional spectral resources. The challenge is to design low complexity and high performance algorithms that capable of accurately detecting the transmitted signals. In this study, the general model of MIMO communication system was introduced in addition to several MIMO Spatial Multiplexing (SM) detection techniques. The BER performance and computational complexity of the optimal and sub-optimal MIMO detection schemes have been analyzed and compared to each other. For ease of understanding and fair comparison, the MIMO detection techniques are categorized into three main categories; viz., linear schemes, successive interference cancelation, and tree-search techniques. Different aspects have been considered and discussed in this evaluation such as; signal to noise ratio, channel matrix conditionality, number of transmit and receive antennas, and other performance limiting factors. The complexity evaluations and performance comparisons and graphs have been generated using an optimized simulator. This simulator has been developed using MATLAB® platform, hence, it can be considered as a reference implementation for any further research on the field of MIMO SM detection.