| Paper ID | D6-S6-T2.1 |
| Paper Title |
Semi-Blind Channel Estimation for RIS-Aided Massive MIMO: A Trilinear AMP Approach |
| Authors |
Zhen-Qing He, University of Electronic Science and Technology of China, China; Hang Liu, The Chinese University of Hong Kong, China; Xiaojun Yuan, University of Electronic Science and Technology of China, China; Ying-Jun Angela Zhang, The Chinese University of Hong Kong, China; Ying-Chang Liang, University of Electronic Science and Technology of China, China |
| Session |
D6-S6-T2: Massive MIMO Channel Estimation |
| Chaired Session: |
Monday, 19 July, 23:40 - 00:00 |
| Engagement Session: |
Tuesday, 20 July, 00:00 - 00:20 |
| Abstract |
This paper studies semi-blind channel estimation for a reconfigurable intelligent surface (RIS) aided uplink massive multiple-input multiple-output (MIMO) system, in which the base station simultaneously estimates the channel coefficients and detects the partially unknown transmit symbols. We formulate the semi-blind channel estimation task as a trilinear inference problem. Based on the approximate message passing (AMP) principle, we develop a computationally efficient approach, called Trilinear AMP, to calculate the marginal posterior mean estimators of the trilinear inference problem. Simulation results demonstrate the effectiveness of the proposed Trilinear AMP approach.
|
