Recent development in wireless communication system attracts great attentions and is in demand of higher system capacity, higher throughput and better quality of service. Multiple-input multiple-output (MIMO) systems have been popular since its proposal as it can meet the high spectral efficiency demands by utilizing multiple antennas on both the transmitter and receiver of the communication system. However, the use of special multiplexing raises another issue at the receiver side of how to detect the transmitted symbol out of the multiplexed data streams efficiently....[ Read more ]

Recent development in wireless communication system attracts great attentions and is in demand of higher system capacity, higher throughput and better quality of service. Multiple-input multiple-output (MIMO) systems have been popular since its proposal as it can meet the high spectral efficiency demands by utilizing multiple antennas on both the transmitter and receiver of the communication system. However, the use of special multiplexing raises another issue at the receiver side of how to detect the transmitted symbol out of the multiplexed data streams efficiently.

In hard output MIMO system, there are two kinds of MIMO detector, which use k-best search and depth-first search. K-best method expands nodes in a parallel way and provides stable output data rates but costs more time than depth-first search, while depth-first search operates in a sequential way but results in variable throughput. The two schemes have different architectures. We develop a configurable architecture that can support both k-best method and depth-first search. In order to resolve the unstable throughput of depth-first search, a block constraint depth-first scheme has been proposed in the literature; however, its performance is not good enough. We propose a hybrid algorithm combining the block constraint depth-first search and k-best method together, which is showed to provide better performance and with invariable throughput. The hybrid algorithm can work using the configurable architecture, which has little hardware overhead comparing with the depth-first search.