Handover decision and Load balancing in LTE networks using a Fuzzy logic system based on an optimisation technique

Abstract

Abstract In the rapidly evolving landscape of LTE networks, achieving efficient Quality of Service (QoS) while ensuring seamless handovers and optimal Load balancing poses a significant challenge. Traditional methods rely on manual decision-making processes, leading to errors and suboptimal performance. Our study explores automated decision-making leveraging LTE networks' self-organising network (SON) capabilities to address this. This research identifies a critical gap in the existing literature: the lack of an automated, error-sensitive system that can swiftly balance the demands of handover and load distribution while maintaining QoS standards. An innovative strategy utilising fuzzy logic systems is suggested to close this gap. Fuzzy logic considers diverse network parameters, enabling it to make informed decisions regarding handovers and Load balancing based on real-time network status and associated variables. Our solution uses cutting-edge optimisation methods like the Whale Optimization Algorithm (WOA) to optimise judgments based on fuzzy logic. These algorithms step in when fuzzy logic encounters complexities, ensuring precise decision-making even in intricate scenarios. The core motivation behind this research lies in the ever-increasing demand for high data rates while preserving QoS standards. A dense LTE cell becomes imperative, necessitating sophisticated algorithms for continuous handover operations. The contribution to the fuzzy logic system's conceptualisation and practical application, which significantly enhances system performance and user mobility, is equally important. Our suggested model fulfils and exceeds the desired QoS by automating the decision-making process and incorporating optimisation approaches, resulting in a smooth and effective LTE network operation.