Apriori-LLR-Threshold-Assisted K-Best Sphere Detection for MIMO Channels

—When the maximum number of best candidates retained at each tree search level of the K-Best Sphere Detection (SD) is kept low for the sake of maintaining a low memory requirement and computational complexity, the SD may result in a considerable performance degradation in comparison to the full-search based Maximum Likelihood (ML) detector. In order to circumvent this problem, in this contribution we propose a novel complexity-reduction scheme, referred to as the Apriori-LLRThreshold (ALT) based technique for the K-best SD, which was based on the exploitation of the a priori LLRs provided by the outer channel decoder in the context of iterative detection aided channel coded systems. For example, given a BER of 10−5 , a nearML performance is achieved in an (8×4)-element rank-deficient 4-QAM system, despite imposing a factor two reduced detection candidate list generation related complexity and a factor eight reduced extrinsic LLR calculation related complexity, when compared to th...

• Type: Conference
• Year: 2008
• Where: VTC
• Authors: Li Wang, Lei Xu, Sheng Chen, Lajos Hanzo
• Keywords: Communications, Computational Complexity, Detection, Sphere Detection, VTC 2008