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Beyond Max-SNR: Joint Encoding for Reconfigurable Intelligent Surfaces

Abstract : A communication link aided by a Reconfigurable Intelligent Surface (RIS) is studied, in which the transmitter can control the state of the RIS via a finite-rate control link. Prior work mostly assumed a fixed RIS configuration irrespective of the transmitted information. In contrast, this work derives information-theoretic limits, and demonstrates that the capacity is achieved by a scheme that jointly encodes information in the transmitted signal as well as in the RIS configuration. In addition, a novel signaling strategy based on layered encoding is proposed that enables practical successive cancellation-type decoding at the receiver. Numerical experiments demonstrate that the standard max-SNR scheme that fixes the configuration of the RIS as to maximize the Signal-to-Noise Ratio (SNR) at the receiver is strictly suboptimal, and is outperformed by the proposed strategies at all practical SNR levels.
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https://hal-centralesupelec.archives-ouvertes.fr/hal-03766455
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Submitted on : Thursday, September 1, 2022 - 10:23:11 AM
Last modification on : Monday, September 12, 2022 - 12:04:47 PM

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Roy Karasik, Osvaldo Simeone, Marco Di Renzo, Shlomo Shamai Shitz. Beyond Max-SNR: Joint Encoding for Reconfigurable Intelligent Surfaces. 2020 IEEE International Symposium on Information Theory (ISIT), Jun 2020, Los Angeles, United States. pp.2965-2970, ⟨10.1109/isit44484.2020.9174060⟩. ⟨hal-03766455⟩

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