Appraisal of Interference Mitigation Techniques in Heterogeneous Networks

Abstract

The increasing complexity and densification of modern cellular networks, particularly in Heterogeneous Network (HetNet) deployments, have intensified the challenge of intercell interference (ICI), necessitating more advanced and adaptive mitigation strategies. This study presents a comprehensive survey of interference management techniques in HetNets, examining both conventional and emerging methods used across LTE and 5G networks. The work begins by defining key interference types and performance metrics such as SINR, throughput, latency, and packet loss. It then classifies various mitigation strategies into resource allocation techniques, power control, antenna and beamforming methods, scheduling and cell association mechanisms, machine learning-based solutions, cooperative CoMP techniques, and interference cancellation approaches. A comparative analysis is conducted to evaluate the strengths, limitations, and implementation considerations of each technique, including AI-enhanced models such as reinforcement learning and neural networks. Further, the study discusses existing gaps and future research directions, emphasizing the need for real-time, intelligent, and scalable interference coordination solutions in ultra-dense and high-frequency (mmWave and THz) environments. The findings underscore that while traditional methods remain foundational, intelligent and self-organizing systems will be crucial to managing interference in the next generation of HetNets.