Near-ML MIMO Detection Algorithm With LR-Aided Fixed-Complexity Tree Searching

In this paper, we propose a low-complexity multiple-input multiple-output (MIMO) detection algorithm with lattice-reduction-aided fixed-complexity tree searching which is motivated by the fixed-complexity sphere decoder (FSD). As the proposed scheme generates a fixed tree whose size is much smaller than that of the full expansion in the FSD, the computational complexity is reduced considerably. Nevertheless, the proposed scheme achieves a near-maximum-likelihood (ML) performance with a large number of transmit antennas and a high-order modulation. The experimental results demonstrate that the performance degradation of the proposed scheme is less than 0.5 dB at the bit error rate (BER) of 10(-5) for a 8 x 8 MIMO system with 256 QAM. Also, the proposed method reduces the complexity to about 1.23% of the corresponding FSD complexity.