摘要
为了使最大似然(ML)检测达到更小的计算复杂度,构建基于非中心卡方分布最大值的球形译码(SD)检测算法,并展开仿真测试来达到最优误码性能。研究结果得到:无论在何种算法下,随着信噪比的增加,误比特率均表现出单调减小的变化规律,变化都平缓。当天线数量变化后,采用不同检测算法得到具有良好重合状态的曲线,其中MSD与ESD达到最优检测性能。在Nt≤Nr条件下,采用改进算法可以获得比ML检测与SD检测更低的复杂度,特别是对于低信噪比情况具有更明显的优势。在Nt>N的条件下,MSD复杂度比TSD减小近20%,ESD相关复杂度可以比MSD降低2%左右。
In order to reduce the computational complexity of maximum likelihood(ML) detection, the spherical decoding(SD) detection algorithm based on the maximum value of non-central chi-square distribution is constructed, and the simulation test is carried out to achieve the optimal error performance. The results show that the bit-error rate decreases monotonically with the increase of signal-to-noise ratio(SNR) in any algorithm. After the number of antennas changes, different detection algorithms are adopted to obtain curves with good coincidence state, in which MSD and ESD achieve the optimal detection performance. Under the condition of Nt Nr, the improved algorithm can achieve lower complexity than ML detection and SD detection, especially for low SNR.Under the condition of Nt > N, the complexity of MSD is nearly 20% lower than that of TSD, and esd-related complexity is about 2% lower than that of MSD.
作者
崔校瑞
CUI Xiao-rui(School of Electric Power,South China University of Technology,Guangzhou 510641 China)
出处
《自动化技术与应用》
2019年第12期154-156,159,共4页
Techniques of Automation and Applications
关键词
球形译码
检测算法
最大似然
计算复杂度
spherical decoding
detection algorithm
maximum likelihood
computational complexity
