Precoder design for improving the performance of MUSIC-based angle-of-arrival estimator
Zhang Li, Yong Huat Chew, Wai‐Choong Wong · 2011
In this paper, we propose a novel algorithm to improve the accuracy in estimating the angle-of-arrival (AoA) when the MUSIC (MUltiple SIgnal Classification) algorithm is used. An optimal precoder, with the objective to minimize the estimation errors of the AoAs, is first derived. However, to compute the optimal precoder requires the channel state information (CSI) exclusive of the receiver array, which cannot be separately estimated practically. A more feasible precoder design approach, which leverages on the feedback instantaneous CSI estimated at the receiver, is next proposed. Using the ideal optimal design to benchmark the performance, our simulation shows that the proposed practical precoder can achieve near-optimal performance, and both can achieve about 4-6 dB improvement in signal-to-noise ratio (SNR) compared to the case when only MUSIC algorithm is applied without precoding. Finally, the performance of the AoA estimator under channel estimation errors is studied through simulation, to demonstrate the robustness of the proposed approach.