摘要
对空时分组码参数识别算法中惩罚函数的选取进行讨论研究,利用改进的AIC准则结合假设检验理论对惩罚函数进行数值分析,提出了一种改变加权因子的空时分组码参数识别算法,在不增加计算复杂度的前提下,提升空时分组码盲识别的性能。仿真结果表明,改进算法比原算法有2d B的性能提升,在低信噪比和小数据量条件下的识别性能优势明显,并且对不同调制方式同样具有较好的鲁棒性。
The choice of penalty function of block space code parameter recognition algorithm is studied, which is discussed via numerical analysis by considering the improved Akaike Information Criterion and the theory of hypothesis test. A modified block space code parameter recognition algorithm is proposed, which could improve the performance with almost no increase in computational com- plexity. Simulation shows that, compared with the original algorithm, the improved algorithm has an improvement of 2dB in perfomance and obvious advantages for the case of low Signal to Noise Ratio and small data size. The results also exhibit good robustness for different kinds of modulation.
出处
《信息工程大学学报》
2016年第4期454-458,共5页
Journal of Information Engineering University
基金
国家自然科学基金资助项目(61401511)
关键词
空时分组码盲识别
多输入多输出
码参数识别
Akaike信息论准则
blind recognition of space-time block code
multiple input multiple output
code parameter recognition
Akaike Information Criterion
