Learning-Based Hybrid RIS Networks for Energy Efficient Information Transfer

There have been numerous studies to develop intelligent radio environments for new use cases and demanding requirements beyond 5G. Reconfigurable Intelligent Surface (RIS) has attracted the attention of several researchers because of its ability to manipulate the electromagnetic characteristics of a wireless channel thereby building a smart radio environment. RIS can be added to improve coverage and establish high-capacity in future wireless networks. In this paper, we discuss how the different network nodes have evolved across different 3GPP Releases to enhance coverage. Moreover, we propose a learning based hybrid RIS network which ensures energy efficiency along with coverage extension of a given network. Simulation results encapsulate the performance gains of RIS in terms of achievable rate and power in FR1 (sub 6 GHz) and FR3 (7-24 GHz) bands.