Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications
Li Wei, Chongwen Huang, George C. Alexandropoulos, Chau Yuen, Zhaoyang, Zhang, and M\'erouane Debbah

TL;DR
This paper proposes novel iterative channel estimation algorithms for RIS-empowered multi-user MISO systems, demonstrating their effectiveness and robustness through simulations and theoretical bounds.
Contribution
It introduces two new algorithms for channel estimation in RIS systems, including an ALS-based method that achieves the CRB and outperforms benchmarks.
Findings
Algorithms outperform benchmark schemes
ALS-based method achieves the CRB
Sum rate approaches perfect channel performance
Abstract
Reconfigurable Intelligent Surfaces (RISs) have been recently considered as an energy-efficient solution for future wireless networks due to their fast and low-power configuration, which has increased potential in enabling massive connectivity and low-latency communications. Accurate and low-overhead channel estimation in RIS-based systems is one of the most critical challenges due to the usually large number of RIS unit elements and their distinctive hardware constraints. In this paper, we focus on the uplink of a RIS-empowered multi-user Multiple Input Single Output (MISO) uplink communication systems and propose a channel estimation framework based on the parallel factor decomposition to unfold the resulting cascaded channel model. We present two iterative estimation algorithms for the channels between the base station and RIS, as well as the channels between RIS and users. One is…
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Taxonomy
MethodsAdaptive Label Smoothing
