基于张量分解的大规模多输入多输出天线预编码

Massive MIMO antenna precoding based on tensor decomposition

提出基于张量分解的大规模多输入多输出(MIMO)天线预编码方案,利用张量分解对高维天线发送数据的降维,保持数据的低秩多维结构特征,获得更加有效的数据表示;同时,通过联合天线和用户信号的空域和时域的相关性,实现发射分集,克服大规模MIMO信道衰落和降低发射误码.通过仿真结果表明该方案适用于大规模MIMO系统.在相同条件下,与传统方案相比,误比特率更低.

A massive multiple input multiple output(MIMO)antenna precoding scheme based on tensor decomposition is proposed.The tensor decomposition is used to reduce the dimension of high-dimensional antennas,and the low-rank multidimensional structure characteristics of the data are maintained,so as to obtain more effective data representation.At the same time,by combining the correlation between the antenna and the airspace and time domain of users,to achieve transmit diversity,and to overcome massive MIMO channel fading and reduce transmission errors.The simulation results show that the proposed scheme is suitable for massive MIMO system.Under the same conditions,the bit error rate is lower than that of the traditional scheme.