Beyond Max-SNR: Joint Encoding for Reconfigurable Intelligent Surfaces

Roy Karasik (1) , Osvaldo Simeone (2) , Marco Di Renzo (3) , Shlomo Shamai (1)

1 EE-Technion - Department of Electrical Engineering - Technion [Haïfa]
2 King‘s College London
3 L2S - Laboratoire des signaux et systèmes

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.

Domaines: Traitement du signal et de l'image [eess.SP]

Roy Karasik, Osvaldo Simeone, Marco Di Renzo, Shlomo Shamai. Beyond Max-SNR: Joint Encoding for Reconfigurable Intelligent Surfaces. IEEE International Symposium on Information Theory, Jun 2020, Los Angeles, United States. ⟨10.1109/isit44484.2020.9174060⟩. ⟨hal-03020727⟩