Computational complexity reduction of MLD based on SINR in MIMO spatial multiplexing systems

Recently, MIMO spatial multiplexing systems have attracted a lot of attention because of their high spectral efficiencies. In MIMO spatial multiplexing systems, maximum likelihood detection (MLD) is known as an optimal method for signal detection in terms of bit error rate (BER). However, the main drawback of MLD is its high complexity. In this paper, we propose two reduced complexity signal detection schemes. One combines the minimum mean square error (MMSE) detection and MLD based on the estimated signal to interference plus noise ratio (SINR). The other combines the ordered successive MMSE detection (OSD) and MLD based on the estimated SINR. We refer to these detection schemes as MMSE-MLD and OSD-MLD, respectively. We show by simulation results that the proposed MMSE-MLD and OSD-MLD can attain almost identical performance to that of MLD, with less complexity.