Adaptive High-Resolution Channel Estimation Approach for Millimeter Wave MIMO Systems

Abstract

Channel estimation is crucial in millimeter wave (mmWave) communication systems. The conflict between high angular resolution and heavy training overhead is a bottleneck to apply beam training-based channel estimation schemes such as hierarchical search and compressed sensing. In this paper, a novel two-stage adaptive high-resolution channel estimation (AHRCE) approach is proposed for mmWave system. In the first stage, hierarchical search based on normal-resolution codebooks is exploited to acquire the coarse estimated multipath components (MPCs). The number of measurements can be dynamically adjusted among training levels. In the second stage, a sparse signal recovery method to achieve high-resolution angles of departure (AoDs) and angles of arrival (AoAs) is introduced. The accurately estimated channel is estimated without quantization error by calculating a set of ratio metrics. Numerical results show that our proposed scheme achieves a more efficient tradeoff between the training overhead and mean square error (MSE) performance in broader SNR region than the other existing method.