Improved k-best sphere decoding algorithms for MIMO systems

Multiple-input multiple-output (MIMO) technique is a key enabling technology for today´s high-rate wireless communications. The sphere decoding algorithm (SDA) has been used for maximum likelihood (ML) detection in MIMO systems. However, it suffers from variable computation complexity and non-fixed throughput. Therefore, the k-best sphere decoding algorithm is proposed for MIMO detections for its less complexity and fixed throughput. The disadvantage for k-best SDA is that it has performance loss due to the reason that ML detection is not guaranteed. In this paper, we propose some improved k-best sphere decoding algorithms which improve the MIMO detection performance. Simulation results show that by applying sorted QR decomposition for the channel matrix, and/or introducing dynamic K values for different layers, our improved algorithms can achieve 1-2 dB detection performance gain for 4 times 4 64QAM MIMO systems over the traditional k-best SDA without introducing extra computational complexity