A Reduced Complexity K-Best SD Algorithm Based on Chi-Square Distribution for MIMO Detection

A reduced K-best sphere decoding (K-best SD) algorithm for Multiple-Input Multiple-Output (MIMO) detection is proposed. The algorithm reduces the complexity of the K-best SD by combining the statistics character of the signal and the requirement of the quality of service (QoS). In the reducing processing of the proposed algorithm, the chi-square distribution (CSD) property of the signal, the optimal symbol error rate (SER) property and the loss of pruning are considered together to give a theoretic error bound and then a threshold to determined which route can be pruned to reduced the calculation complexity. The algorithm reduces the complexity with a controllable cost of performance decrease. Simulation results on a 16QAM system with 4×4 antennas show that the algorithm can attain the near-optimal performance with a significant complexity reduction comparing to the original K-best SD or maximum likelihood (ML) algorithm.