Year: 2025
Type: article
Abstract: — The rapid deployment of 5G networks has introduced new challenges in coverage limitations, power consumption, and signal attenuation, especially in urban environments. To address these issues, this research explores the integration of a 64×64 MIMO array with Reconfigurable Intelligent Surfaces (RIS) to enhance network coverage while reducing power consumption. MIMO technology improves spectral efficiency and enables beamforming, directing signals toward users for better connectivity. However, the high power requirements of MIMO systems make them less energy-efficient. RIS, a passive metasurface-based technology, helps in reflecting and redirecting signals without consuming excessive power. By strategically placing RIS panels, we can optimize signal propagation, reduce path loss, and improve overall network efficiency. This study analyzes different system configurations, including standalone 64×64 MIMO, individual RIS panels, and a hybrid MIMO-RIS setup. Results show that: • A 64×64 MIMO system provides strong coverage but at high power consumption. • RIS panels reduce power usage but have limited coverage individually. • A hybrid system combining MIMO and RIS offers the best balance, significantly extending coverage while lowering energy consumption. Simulation results confirm that the hybrid system improves coverage area by nearly 100% while reducing power consumption by up to 60% compared to traditional MIMO setups. Additionally, optimizing RIS placement and reflection angles further enhances signal quality and minimizes interference. This research provides a practical and energy-efficient solution for 5G coverage enhancement. Future work will focus on real-world implementation of RIS in 5G networks and potential applications in next-generation wireless communication technologies. Keywords— Metasurface, millimeter wave, path-loss model, reconfigurable reflector, reconfigurable intelligent surface (RIS), wireless communication
DOI: 10.55041/ijsrem46144
Author: Aditya Patil
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409838311