一种新型低复杂度双层分组天线选择算法

A novel low-complexity two-tier group antenna selection algorithm

针对平坦相关瑞利衰落信道环境下的端到端大规模MIMO系统复杂度过高的问题,提出一种基于离散布谷鸟搜索的低复杂度双层分组天线选择算法。该算法首先基于天线信道相关性对大规模天线阵列进行分组处理,进而利用新型双层算法对分组的天线集合进行优化天线选择。其中,新型双层算法的第一层是每小组天线基于离散布谷鸟搜索的内部选择,第二层是对第一层选择的所有天线利用离散布谷鸟搜索进行最终的选择。提出的新型天线选择算法可有效降低大规模MIMO系统复杂度。仿真结果验证了在平坦相关瑞利衰落信道环境下,提出的天线选择算法能够以较低选择复杂度获得接近最优选择方法的容量性能和较优的BER性能。

Aiming at the high complexity of the end-to-end massive MIMO systems in flat correlated Rayleigh fading channel environments,a low-complexity two-tier group antenna selection algorithm based on discrete cuckoo search was proposed.The algorithm firstly grouped large-scale antenna arrays based on the correlation of antenna channels,and then used a new two-tier algorithm to optimize antenna selection for the grouped antenna sets.The first layer of the new two-tier algorithm was the internal selection of each group of antennas based on discrete cuckoo search,and the second layer was the final selection of all antennas selected by the first layer using discrete cuckoo search.The novel antenna selection algorithm could effectively reduce the complexity of large-scale MIMO systems.The simulation results verify that the antenna selection algorithm can obtain the capacity performance close to the optimal selection method and better BER performance with lower selection complexity under the flat correlated Rayleigh fading channel environments.