deploying Reconfigurable Intelligent Surfaces for Interference Reduction

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A 1,000-fold mobile data traffic growth was predicted from 2020 to 2030, with more than 80% of that happening indoors. Emerging indoor applications of the sixth generation of mobile communication (6G) place higher requirements on 6G indoor network capacity. Reconfigurable intelligent surface (RIS), one of the promising technologies identified for 6G, has the potential to address the 6G indoor network capacity requirement. RIS has attracted a lot of interests with a focus on coverage extension. However, the Fellow believes that enhancing network capacity by reducing interference is the most promising use case for RIS. In order to realise the full potential of RIS for interference reduction, the following challenges need to be addressed urgently. (1) How to identify interference paths for typical indoor environments to guide RIS deployment for interference reduction? (2) How to optimally place RISs (e.g., number and location) to absorb interference? (3) What is the upper bound of network capacity for a wireless network involving RISs? and (4) Which indoor scenarios will benefit from RIS deployment from a life-cycle point of view? To address the above challenges, the Fellow has defined the following research and innovation (R&I) objectives: (1) To model interference paths and distributions in typical indoor scenarios; (2) To find optimal deployment of RISs to enhance the indoor wireless network capacity; (3) To obtain the capacity upper bounds for networks involving RISs; and (4) To quantify the life-cycle benefits of RIS deployment for typical indoor scenarios. Achieving the above objectives will reveal the topology of interference paths in indoor environments so that to provide candidate locations for RIS deployment, develop an optimisation framework and associated algorithms for RIS deployment, quantify the capacity enhancement, and identify the most promising indoor scenarios for RIS deployment.