A Systemic Review of Interference Reduction and Management Techniques in Cellular Network

Abstract

The increase of interference in cellular network makes the development of efficient interference management techniques a key enabler. But, as we move towards denser networks, interference management is becoming increasingly challenging. In modern times, communications technologies serve as the driver of social, economic and political developments. But, interference in the communication networks comes as undesirable nuisance. In this paper, techniques employed in the management of interference encountered in cellular networks are reviewed systemically. Propositions by different authors including intermodulation solutions, frequency planning methods, genetic algorithms, simulated annealing models, ant colony and multi-agent optimization, artificial neural networks model and evolutionary strategy approach (EAs), are X-rayed. Despite all efforts, challenges of interference still abound in communication networks. Among several techniques available to address interference networks, EAs has been given wider applications and the result shows good performance of the technique. Meanwhile, genetic algorithm is also efficient where applied, but to reduce interference to the minimum in the current and future cellular networks, this paper proposes synchronization of reduction techniques, where traffic-driven factors are considered.