Differential Data-Aided Beam Training for RIS-Empowered Multi-Antenna Communications
Kun Chen-Hu, George C. Alexandropoulos, Ana Garc\'ia Armada

TL;DR
This paper introduces a zero-overhead, data-driven beam training method for RIS-enabled multi-antenna systems that eliminates the need for reference signals, improving efficiency especially in high mobility scenarios.
Contribution
It proposes a novel non-coherent data transmission scheme for RIS beam training that removes the need for reference signals, enhancing spectral efficiency and system performance.
Findings
The proposed NCDS-based method outperforms traditional CDS in efficiency and complexity.
Analytical expressions for SINR in non-coherent RIS systems are derived.
Simulations confirm the accuracy and superior performance of the proposed approach.
Abstract
The Reconfigurable Intelligent Surface (RIS) constitutes one of the prominent technologies for the next generation of wireless communications. It is envisioned to enhance the signal coverage in cases when the direct link of the communication is weak. Recently, beam training based on codebook selection is proposed to obtain the optimized phase configuration of the RIS. After that, the data is transmitted and received by using the classical coherent demodulation scheme (CDS). This training approach is able to avoid the large overhead required by the channel sounding process, and it also circumvents complex optimization problems. However, the beam training still requires the transmission of some reference signals to test the different phase configurations of the codebook, and the best codeword is chosen according to the measurement of the received energy of the reference signals. Then, the…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Advanced Antenna and Metasurface Technologies · Antenna Design and Analysis
