基于空间递推的毫米波信道一致性仿真算法研究

Millimeter-wave channel simulation algorithm with consistency based on spatial recursion

根据鸟巢28 GHz信道测量数据,提出了一种基于空间递推的空间一致性信道大尺度参数(largescale parameter, LSP)生成算法--空间递推算法(spatial recursion algorithm, SRA),并与传统的WINNER Ⅱ算法进行了比较. SRA利用多维正态分布,通过特定的递推算法依次生成各个仿真点的信道LSP,以实现参数的自相关与互相关特性.结果表明,在实现空间一致性的前提下,SRA仿真结果与测量数据高度吻合,仿真精度优于WINNER Ⅱ算法,且SRA无需单独生成参数互相关特性,仿真步骤更为简单. SRA为相关算法的研究提供了一种新的思路,对毫米波时变信道仿真有重要意义.

Based on the Bird’s Nest 28 GHz channel measurement data, this paper proposes a spatially consistent channel large-scale parameter generation algorithm based on spatial recursion, and compares it with the traditional WINNER Ⅱ algorithm. This algorithm uses multi-dimensional normal distribution and specific recursion algorithm and generates the channel large-scale parameters of each simulation point sequentially, to realize the auto-correlation and cross-correlation characteristics of the parameters. The results show that, on the premise of achieving spatial consistency, the simulation results of the spatial recursive parameter generation algorithm are highly consistent with the measured data, the simulation accuracy of this algorithm is better than the WINNER II algorithm. Compared with the WINNER Ⅱ algorithm, the spatial recursive parameter generation algorithm does not need to generate the parameter cross-correlation characteristics separately, which simplifies the simulation steps. The spatial recursive parameter generation algorithm provides a way for the research of related algorithms. This new idea is of great significance for millimetre-wave time-varying channel simulation.