Enhanced Programmability of Reconfigurable Intelligent Surfaces for Smart Cities using Application-Specific Integrated Circuits
Reconfigurable Intelligent Surfaces (RISs) are emerging as a key technology for enhancing wireless communications in smart city environments, offering robust, low-latency connectivity. This paper presents the design of an adaptive control system based on high-voltage, mixed-signal integrated circuits for controlling tunable RISs, tailored for wireless cellular communications in urban areas. The proposed system enables enhanced programmability by dynamically steering beams and fine-tuning signal reflections through the precise control of varactor diodes embedded within the RIS unit cells. This flexible system architecture supports real-time software reconfiguration, allowing RIS units to adapt to varying network conditions and scale seamlessly across smart city infrastructures. Simulated results on a 0.35 μm CMOS high voltage process technology demonstrate the circuit's ability to achieve low power consumption and high reconfiguration speed across a wide temperature range. The control electronics are separated from the RIS panels, this way enabling tiling of multiple surfaces for scalable, cost-effective deployment. This approach offers a promising pathway to meeting the growing demand for seamless, high-speed, and energy-efficient connectivity in next-generation smart city applications, including vehicular networks, Internet of Things, smart traffic management and smart infrastructure.
Authors
- Yorgos Stratakos
- Marco A. Antoniades (ORCID: https://orcid.org/0000-0002-9699-2387)
- Loukas Petrou (ORCID: https://orcid.org/0000-0003-1999-5733)
- Anastasis Kounoudes (ORCID: https://orcid.org/0000-0001-6282-2200)
- Julius Georgiou (ORCID: https://orcid.org/0000-0002-7474-5449)
- Konstantinos Michail
- Thorsten Brandt
- Panos Megerditchian
Institutions
- University of Cyprus (CY)
- SignalGeneriX (Cyprus) (CY)
- Toronto Metropolitan University (CA)
Publication Details
- Published
- 2025-05-25
- DOI
- https://doi.org/10.1109/iscas56072.2025.11043875
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Research and Innovation Foundation