Dynamic Coverage Optimization Using 3D Position-Controlled Reconfigurable Intelligent Surfaces in 6G Networks
Abstract
Reconfigurable Intelligent Surfaces (RIS) are one of the promising technologies in wireless communications. They allow controlling how wireless signals are reflected on smart surfaces, which helps improve coverage and increase network efficiency. Although most current research use RIS models fixed to walls, but this design may not always be the best option for achieving optimal coverage, especially in environments where user density changes frequently. In this research, we propose an adaptive RIS model that can change both the vertical height and the horizontal steering angle (azimuth) in an intelligent way, based on user locations or the load in each area. This model is supported by signal quality indicators such as the Received Signal Strength Indicator (RSSI), which is measured at the user side and used as feedback to determine the best RIS orientation. The proposed RIS model was implemented in MATLAB and tested in two scenarios according to user locations, comparing the performance of a fixed RIS with that of an adaptive moving RIS. Simulation results for both scenarios showed that increasing the RIS height from 5 to 15 meters helped double the received signal power for some users, while adjusting the horizontal steering angle from 0° to 45° increased the received power from -104 dB to -94 dB, which is more than eight times the power in the case of a fixed RIS. These results confirm that using a 3D repositionable RIS is a practical step toward improving wireless performance system, especially in 6G environments that are complex and continuously changing.
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