Laue F, Jamali V, Schober R (2023)
Publication Language: English
Publication Type: Conference contribution
Publication year: 2023
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 1164-1169
Conference Proceedings Title: 2023 IEEE Globecom Workshops (GC Wkshps)
ISBN: 9798350370218
DOI: 10.1109/GCWkshps58843.2023.10464537
This paper studies beam training for self-sustainable reconfigurable intelligent surfaces (RISs), where the RIS is en-dowed with energy harvesting capabilities in order to operate independently of external power sources. In particular, we consider codebook-based reconfiguration of the RIS for periodic alignment of the reflection beam with the current location of a mobile user. Moreover, a fraction of the RIS unit cells harvests energy from the incident signal while the remaining unit cells are used for signal reflection. Based on this framework, we analyze the code-book design, beam training overhead, and power consumption. Furthermore, we show that the optimal unit cell split ratio can be obtained based on a convex optimization problem. In addition, for low-overhead beam training, we derive a closed-form expression for the rate loss caused by the energy constraint needed for self-sustainable operation. Finally, we provide simulation results to evaluate the proposed analytical framework and reveal insights on the tradeoff between beam training overhead, RIS response time, and RIS power consumption.
APA:
Laue, F., Jamali, V., & Schober, R. (2023). Beam Training for Self-Sustainable RIS. In 2023 IEEE Globecom Workshops (GC Wkshps) (pp. 1164-1169). Kuala Lumpur, MY: Institute of Electrical and Electronics Engineers Inc..
MLA:
Laue, Friedemann, Vahid Jamali, and Robert Schober. "Beam Training for Self-Sustainable RIS." Proceedings of the 2023 IEEE Globecom Workshops, GC Wkshps 2023, Kuala Lumpur Institute of Electrical and Electronics Engineers Inc., 2023. 1164-1169.
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