基于动态分组的球形译码算法

在MIMO信号检测中,采用最大似然算法可以使系统的误码率最低,但最大似然算法要搜索整个信号空间,计算速度相当慢。球形译码算法性能最接近最大似然算法,它通过减少需要比较的信号点可大大降低计算量。提出了动态分组的球形译码算法,对传统球形译码算法进行了改进。仿真结果表明,所提算法可以根据M IMO系统的需要进行动态调整,可在小信噪比时降低误码率,大信噪比时提高译码速率。

Sphere Decoding Algorithm Based on Dynamic Grouping

Using maximum-likelihood(ML) algorithm in signal detection of MIMO system,the lowest bit error rate(BER) can be achieved,but the ML algorithm needs to search the whole signal space,which makes the computation speed quite low.The sphere decoding algorithm approximates to the ML algorithm in performance.By reducing the number of required comparisons,the decoding complexity is reduced significantly.The simulation results show that the proposed algorithm can make dynamic adjustment according to the need of MIMO system,the bit error rate(BER) is reduced when the signal-to-noise ratio(SNR) is low and the decoding speed is raised when the SNR is high.