摘要
针对传统稀疏重构算法需要信道稀疏度先验信息、复杂度高、不利于实际应用的问题,提出了一种新的基于波束空间分解的稀疏度自适应毫米波信道估计算法。该算法利用毫米波信道稀疏性的特点对信道进行波束空间分解,构造基于码本的感知矩阵,获得l1范数约束问题模型;其次结合分段弱匹配追踪算法,采用弱阈值从感知矩阵筛选原子,再通过分组选择机制对选择的原子进行二次优化;最后根据最小二乘法估计出毫米波信道。仿真结果表明,所提算法的估计精度和复杂度在低信噪比和低训练长度情况下明显优于传统匹配追踪算法。
The traditional sparse reconstruction algorithm needs prior information of channel sparsity and has high complexity,so it is not conducive to practical application.A new sparse adaptive millimeter-wave(MMW)channel estimation algorithm based on beam space decomposition is proposed.The channel matrix is decomposed in beam space,and the sensing matrix based on codebook is constructed to obtain the l1 norm constraint.Combined with the stagewise weak matching pursuit algorithm,the atoms are screened from the sensing matrix by weak threshold,and then the selected atoms are quadratically optimized by group selection mechanism.The MMW channel is estimated according to the least square method.The simulation results show that the estimation accuracy and complexity of the proposed algorithm are obviously better than those of the traditional matching pursuit algorithm under low signal-to-noise ratio and small training length.
作者
申敏
余开文
SHEN Min;YU Kaiwen(School of Communication and Information Engineering,Protocols and System Application,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Innovation Team of Communication Core Chip,Protocols and System Application,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
出处
《电讯技术》
北大核心
2020年第12期1437-1441,共5页
Telecommunication Engineering
基金
国家科技重大专项(2018ZX03001026-002)。
关键词
毫米波MIMO系统
信道估计
压缩感知
匹配追踪算法
millimeter-wave MIMO system
channel estimation
compressed sensing
matching pursuit algorithm
