Reduced Complexity Maximum-Likelihood Detection for MIMO-OFDM Systems

A reduced complexity Maximum-Likelihood (ML) detection algorithm is proposed for the multiple-input multiple-output orthogonal frequency division multiple (MIMO-OFDM) systems. The proposed detection algorithm combines the ML algorithm and the QR algorithm. In the detection process, the first T signals are detected by the ML algorithm and the last Nt-T signals are detected by QR algorithm where T is a parameter and Nt is the number of transmitter antennas. From the simulation results, compared with the traditional ML algorithm, the computational complexity of the proposed algorithm with 4 transmitter antennas, 4 receiver antennas and T=3 is reduced by 95% at the expense of about 1.3dB signal-to-noise-ratio (SNR) degradation for bit error rate (BER) at 10-3. Therefore, the proposed detection algorithm can be used in the practical MIMO-OFDM systems requiring very low complexity.