Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMO

• Published in: IEEE wireless communications letters Vol. 9; no. 2; pp. 210 - 214
• Main Authors: He, Zhen-Qing, Yuan, Xiaojun
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.02.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation algorithms; Array signal processing; Bilinear factorization; Channel estimation; Computer simulation; large intelligent metasurface; massive MIMO; matrix completion; Metamaterials; Metasurfaces; MIMO (control systems); Signal processing; Signal processing algorithms; Sparse matrices
• ISSN: 2162-2337; 2162-2345
• DOI: 10.1109/LWC.2019.2948632

In this letter, we consider the problem of channel estimation for large intelligent metasurface (LIM) assisted massive multiple-input multiple-output (MIMO) systems. The main challenge of this problem is that the LIM integrated with a large number of low-cost metamaterial antennas can only passively reflect the incident signals by certain phase shifts, and does not have any signal processing capability. To deal with this, we introduce a general framework for the estimation of the transmitter-LIM and LIM-receiver cascaded channel, and propose a two-stage algorithm that includes a sparse matrix factorization stage and a matrix completion stage. Simulation results illustrate that the proposed method can achieve accurate channel estimation for LIM-assisted massive MIMO systems.