Mitigating ICI in 5G Technologies

The deployment of 5G cellular networks has brought about unprecedented increases in network capacity and data rates. However, the dense deployment of small cells in 5G networks has also led to a significant rise in inter-cell interference (ICI), which can degrade network performance and user experience. In this project, we propose an AI-based power control approach to mitigate ICI and enhance the overall performance of 5G cellular networks.

Our approach leverages AI model to dynamically adjust the transmit power levels of base stations (BSs) in response to changing network conditions and traffic demands. By continuously learning from the network environment, our AI-based power control algorithm autonomously optimizes power allocation to minimize interference while maximizing network throughput and spectral efficiency. To evaluate the effectiveness of our proposed approach, we conducted extensive simulations using a realistic network model and evaluated its performance under various traffic scenarios and network configurations. Our results demonstrate that the AI-based power control mechanism effectively reduces inter-cell interference, improves network throughput, and enhances overall network capacity compared to traditional power control methods. Furthermore, we conducted real-world experiments using a testbed implementation of our AI-based power control algorithm in a 5G cellular network environment. The experimental results validate the effectiveness and practical feasibility of our proposed approach in mitigating inter-cell interference and optimizing network performance.