Energy Efficient Low-Complexity RIS-Aided 3-D DoA Estimation and Target Tracking Algorithm via Matrix Completion

In this paper, we propose an algorithm for fast direction-of-arrival (DoA) tracking in reconfigurable intelligent surface aided systems. We reduce the total power consumption by reducing the number of radio-frequency chains in the access point, which leads to signal data loss and consequently inaccurate DoA estimation. The incomplete signal data is recovered by the truncated nuclear norm regularization alternating direction method of multipliers algorithm. The adopted iterative matrix completion algorithm is robust and fast, hence suitable for DoA tracking applications. In order to reduce the high computational cost of the subspace DoA estimation algorithms, a novel adaptive forgetting factor (AF) recursive least squares algorithm is proposed for fast DoA estimation and tracking. The adaptive moment estimation method is adopted for low-complexity AF update. The proposed algorithm is evaluated and compared with the state-of-the art algorithms under single-path propagation and multi-path propagation conditions. Based on the analysis and simulation results, after applying matrix completion, the proposed DoA estimation and tracking algorithm outperforms the state-of-the-art algorithms.