摘要
针对大规模MIMO系统信道的稀疏性并且信道随时间缓慢变化的特性,提出了一种自适应信道估计算法。算法根据前一个符号的信道非零抽头索引集(先验支持集),利用质量参数衡量先验支持集的质量,自适应估计当前符号的稀疏索引集(支持集)及时域信道脉冲响应(CIR)。仿真结果证明:提出的算法能够有效提升信道估计的精度,对信道时延变化具有更好的适应性。
An adaptive channel estimation algorithm is proposed in massive MIMO systems for sparsity and slow time variant of the channels. By exploiting non-zero-tap sparse index set of the channel information estimated by the previous symbols( prior support) and using a quality parameter to measure the quality of the prior support,the algorithm adaptively estimated sparse index set( support) and timedomain channel impulse response( CIR) of the current symbols. The simulation results provided to demonstrate that the proposed algorithm effectively improves the accuracy of channel estimation and has better adaptability to channel delay variation.
出处
《信息技术》
2018年第2期59-61,67,共4页
Information Technology
基金
国家重大仪器专项(6142780130)
