面向5G/6G大规模MIMO信道实时模拟研究

针对FPGA平台模拟大规模多输入多输出(Multiple-Input Multiple-Output, MIMO)信道存在资源消耗大及实时性差的问题,基于谐波叠加结构的非平稳MIMO 离散信道模型,提出了一种高效的迭代算法,实时产生多支路复指数信号。引入定点化误差补偿算法和时分复用结构,保证了输出信道衰落的精度并优化了硬件资源消耗。采用所提方法实现单通道信道衰落的模拟,与传统LUT 方法和CORDIC 方法相比,资源消耗率分别降低了6.64%和3.4%。将所提算法应用于3GPP标准扩展车载A(Extended Vehicular A model, EVA)信道场景,实测结果表明,信道输出的统计特性如时延功率谱和多普勒功率谱密度与理论结果吻合。经分析和验证,所提算法可用于大规模信道实时模拟研究、验证等领域。

A Real-Time Emulation Research on 5G/6G Massive MIMO Channels

There are several key issues of high resource consumption and poor real-time performance in the existing field programmable gate array (FPGA) platform for multiple-input multiple-output (MIMO) channel emulation. Based onthe non-stationary discrete channel model with sum of sinusoids structure, an efficient iterative method is proposed in this paper to generate massive complex exponential signals in real time. By introducing a fixed-point error compensation algorithm and time-division structure, the accuracy of the output channel fading is guaranteed and the hardware resource consumption is further optimized. For single channel emulation, the resource consumption is significantly reduced 6.64% and 3.64% compared with the traditional LUT and CORDIC method respectively. According to 3GPP standard Extended Vehicular A Model (EVA) scenario, measurement results have shown that the statistical properties of the output channel, i.e., power delay profiles (PDP) and Doppler power spectral density (DPSD) are consistent well with the theoretical results. Thus, it can be applied on the real-time performance analysis, design verification of massive channel emulation.