基于高原复杂通信场景下的超大规模MIMO混合场信道估计

Hybrid-Field Channel Estimation on Ultra-Large MIMO in Complex Communicati on Scenarios on Plateau

由于高原地区重山环绕,通信条件较差,会导致通信系统的容量降低,于是通过在基站端部署超大规模的天线阵列,即超大规模多输入输出(Extra-Large Multiple-Input Multiple-Output,XL-MIMO)技术,从而提高通信系统吞吐率。为了能够保证XL-MIMO系统容量,获取准确的信道状态信息至关重要。随着基站天线数的增多,在信道估计过程中会带来较高的导频开销,从而降低通信效率。然而在XL-MIMO系统中,信道具有稀疏的特性,因此文章提出一种基于伍德伯里变换的OMP压缩感知算法来估计信道,从而能够降低导频开销。具体地,传统的OMP算法中有矩阵求逆的操作,然后基于“伍德伯里”变换将矩阵求逆的操作转化成另一种求逆的步骤,通过仿真与传统的OMP算法相比性能上并没有损失,验证了提出来算法的有效性。

That the plateau area surrounded by heavy mountains with poor communication conditionsresults in a decrease of the capacity of the communication system.To address this issue,the ultra-large-scale antenna array at the base station end,known as Extra-Large Multiple-Input Multiple-Output(XL-MIMO)technology is deployed,so as to improve the throughput rate of the communication system.To maintain the XL-MIMO system capacity,it is essential to obtain accurate channel state information.With an increasing number of base station antennas,the pilot overhead will be higher in the channel estimation process,which will reduce the communication efficiency.However,in XLMIMO systems,the channel has the characteristics of sparseness,so this paper proposes an OMP(Orthogonal Matching Pursuit)compressive sensing algorithm based on the Woodbury transform to estimate the channel so as toreduce the pilot overhead.Specifically,the traditional OMP algorithm has the operation of matrix inversion,and then the matrix inversion operation is transformed into another step of inversion based on the Woodbury transform,and the effectiveness of the proposed algorithm is verified by simulation without loss of performance compared with the traditional OMP algorithm.