Joint AoA and Channel Estimation for SIMO- OFDM Systems: A Compressive-Sensing Approach

摘要

Millimeter-wave (mmWave) transmission has been considered in future fifth generation (5G) communication systems. Since the pathloss in mmWave is severe, beamforming with antenna arrays, an enabling technology in the 5G era, will become a must. To conduct receive beamforming, however, we need to know the information about the angle-of-arrival (AoA). In this paper, we consider joint AoA and channel estimation for single-input-multiple-output (SIMO) OFDM systems. As known, wireless channels are sparse, and this is particularly true for mmWave environments. Conventional compressive-sensing (CS) based channel estimation methods only consider single-input-single-output systems. We propose new matching-pursuit-based CS methods for channel estimation in SIMO-OFDM systems, using frequency-domain pilots. With the estimated channels, AoA's are then estimated by the maximum-likelihood method. Since a hidden parameter is involved in the problem, an expectation-maximization (EM) algorithm is then employed. The Cramer-Rao lower bound (CRLB) is also derived for the AoA estimation. Simulation results show that the proposed channel estimation can significantly outperform existing methods while the proposed AoA estimation attains the CRLB.