兼容Wi-Fi感知的自适应波束形成研究

Research on Adaptive Beamforming Compatible with Wi-Fi Sensing

为了优化Wi-Fi自适应波束形成器的性能以提高感知精度,首先阐述最小均方误差和最小二乘准则下的两类自适应波束形成算法,并通过仿真实验分析应用这两类算法的波束形成器在不同阵元数线性阵列的收敛速度和不同信干噪比对算法迭代次数的影响。并针对Wi-Fi感知的时变无线环境,提出RLS-NLMS联合自适应算法权衡波束形成器的收敛速度与跟踪性能,仿真实验结果证明该算法切实可行。

In order to optimize the performance of Wi-Fi adaptive beamformer for improving sensing accuracy, two kinds of adaptivebeamforming algorithms based on the criteria of minimum mean square error and least squares are first elaborated. Simulationexperiments are conducted to analyze the convergence rate of beamformers using these algorithms on linear arrays withdifferent number of elements and the impact of different signal-to-interference-plus-noise ratios on algorithm iterations. For thetime-varying wireless environment perceived by Wi-Fi, an RLS-NLMS joint adaptive algorithm is proposed to trade off theconvergence rate and tracking performance of the beamformer. Simulation results verify the feasibility of the algorithm.