AN ENHANCED FUZZY LOGIC-BASED TECHNIQUE FOR SEAMLESS HANDOFF DECISION IN CELLULAR NETWORKS

Abstract

Seamless handoff in cellular networks is essential to maintain uninterrupted connectivity, especially in heterogeneous and dynamic environments characterized by varying user mobility, network congestion, and interference. This paper proposes a fuzzy logic-based handoff decision-making algorithm that integrates multiple real-time network parameters—Received Signal Strength Indicator (RSSI), Signal-to-Noise Interference Ratio (SINR), network load, and user velocity—into a Mamdani fuzzy inference system (FIS) to optimize handoff efficiency. The proposed system dynamically adapts to changing network conditions to minimize handoff latency, packet loss, jitter, and end-to-end delay while maximizing throughput. Simulation results, implemented in Python Colab using synthetic data, demonstrate that the fuzzy logic approach significantly outperforms traditional RSSI- and SINR-based handoff methods. The fuzzy-enhanced algorithm reduces handoff latency by up to 20%, improves throughput by 30%, and decreases packet loss and end-to-end delay by 25% and 18%, respectively. These findings suggest that fuzzy logic offers a robust, adaptive solution for handoff management in future 5G and beyond networks, enhancing Quality of Service (QoS) and user experience in heterogeneous cellular environments.