A novel low complexity maximum likelihood detection algorithm for MIMO WLAN system

In this paper, we propose a low complexity algorithm for the maximum likelihood detection (MLD) of MIMO systems. Our algorithm separates the In-phase and Quadrature-phase components of a complex signal into two independent real numbers before calculating the Euclidean distance. Whereby, it is able to determine the closest constellation points directly without: 1) searching all of the candidates and 2) sorting all the results as the well-known K-Best sphere decoding (KSD) does. Consequently, its complexity becomes insignificantly affected by the size of the constellation. We simulate the IEEE 802.11 ac system by using the proposed algorithm and other MIMO decoder types such as Linear MMSE, BLAST-MMSE, LRA-MMSE, and KSD. The Bit Error Rate (BER) performance and complexity are exposed and compared. The paper shows that the proposed algorithm significantly reduces the complexity with an insignificant degradation of BER performance as compare to the KSD.