Interference management techniques in cellular networks: A review. Issue 1 (1st January 2017) - Adediran, Y.A.; Lasisi, H.; Okedere, O.B.
Abstract: In modern times, communications technologies serve as the drivers of social, economic and political developments. But, interference in the communication networks comes as undesirable nuisance. In this work, techniques employed in the management of interference encountered in cellular networks are reviewed. Propositions by different Authors include intermodulation solutions, frequency planning methods, genetic algorithms, Simulated annealing models, ordering heuristic, ant colony and multi-agent optimization, artificial neural networks model, evolutionary strategy approach (EAs), and hybrid EAs. While many techniques work more effectively in some areas of operations, others show strong performances in other areas. For instance, the technique of weak cooperation among base station proposed by some authors offer significant network performance when employed as it provides framework for optimal performances of adjacent base stations under some performance objectives. Also evolutionary strategy approach employed by some other authors shows proficiency in the management of channels allocation aimed at minimizing the problems of interference, which can manifest as call blocking or dropping. Furthermore, some authors designed hybrid EAs integrating local search and constraint programming into evolutionary operators, which was shown to speed up performance. 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 results show good performance of this technique. Meanwhile, genetic algorithm is also efficient where applied, but to reduce interference to the minimum in the current and future mobile communication networks, this review proposes synchronization of reduction techniques, where traffic-driven factors are considered.