Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave MIMO Systems
Lin T, Yu X, Zhu Y, Schober R (2020)
Publication Type: Conference contribution
Publication year: 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference Proceedings Title: 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
ISBN: 9781728182988
DOI: 10.1109/GLOBECOM42002.2020.9322519
Abstract
Intelligent reflecting surfaces (IRSs) are regarded as promising enablers for future millimeter wave (mmWave) wireless communication, due to their ability to create favorable line-of-sight (LoS) propagation environments. In this paper, we investigate channel estimation in downlink IRS-assisted mmWave multiple-input multiple-output (MIMO) systems. By leveraging the sparsity of mmWave channels, we formulate the channel estimation problem as a fixed-rank constrained non-convex optimization problem. To tackle the non-convexity, an efficient algorithm is proposed by capitalizing on alternating minimization and manifold optimization (MO), which yields a locally optimal solution. Simulation results show that the proposed MObased estimation (MO-EST) algorithm significantly outperforms two benchmark schemes and demonstrate the robustness of the MO-EST algorithm with respect to imperfect knowledge of the sparsity level of the channels in practical implementations.
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China (CN)How to cite
APA:
Lin, T., Yu, X., Zhu, Y., & Schober, R. (2020). Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave MIMO Systems. In 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc..
MLA:
Lin, Tian, et al. "Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave MIMO Systems." Proceedings of the 2020 IEEE Global Communications Conference, GLOBECOM 2020 Institute of Electrical and Electronics Engineers Inc., 2020.
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