基于±1二次规划的低复杂度球形解码算法

Improved sphere decoding algorithm based on ±1 quadratic programming

从MIMO检测的±1二次规划模型出发,推导了最大似然MIMO检测最优解的必要条件。在此基础上提出了一种基于必要条件的球形解码改进算法,该算法在球形解码剪枝策略的基础上利用必要条件对树型搜索的节点进行进一步剪枝,从而明显降低了运算复杂度,而不降低球形解码检测算法的误比特率性能。

With the ±1 quadratic programming of the MIMO detection, the necessary conditions for MIMO detection optimal solution were derived. An improved sphere decoding algorithm based on these necessary conditions was proposed. The algorithm prunes redundant nodes by necessary conditions based on the origin sphere decoding, With this pruning strategy, the complexity of algorithm is reduced significantly, while holding the bit error rate performance.