Adaptive selection of surviving symbol replica candidates based on maximum reliability in QRM-MLD for OFCDM MIMO multiplexing

The paper proposes an adaptive selection algorithm for surviving symbol replica candidates based on the maximum reliability in ML detection with QR decomposition and M-algorithm (QRM-MLD) for OFCDM MIMO multiplexing. In the proposed algorithm, symbol replica candidates newly-added at each stage are ranked for each surviving symbol replica from the previous stage using multiple quadrant detection. Then, branch metrics are calculated only for the limited number of symbol replica candidates with high reliability based on an iterative loop in increasing order of the accumulated branch metrics from the candidate with the minimum one. Simulation results show that the computational complexity of the proposed algorithm from the viewpoint of the number of real multiplications is reduced to approximately 1/6 and 1/1900, respectively, compared to that of the original QRM-MLD and that of the conventional MLD with squared Euclidian distance calculations for all symbol replica candidates, assuming the identical achievable average block error rate (BLER) performance in 4-by-4 MIMO multiplexing with 16QAM data modulation. The results also show that 1-Gbps throughput is achieved at the E_b/N₀ per receiver antenna of approximately 9 dB using the adaptive selection algorithm in QRM-MLD associated with 16QAM modulation and turbo coding with coding rate of 8/9, assuming a 100-MHz bandwidth for a twelve-path Rayleigh fading channel (rms delay spread, 0.26 μsec; maximum Doppler frequency, 20 Hz).