A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments A multiobjective strategy suitable for Self-Optimizing Networks

• Published in: Wireless networks Vol. 20; no. 6; pp. 1369 - 1386
• Main Authors: González G., David, García-Lozano, Mario, Ruiz, Silvia, Lee, Dong Seop
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.08.2014; Springer; Springer Nature B.V
• Subjects: Algorithmics. Computability. Computer arithmetics; Analysis; Applied sciences; Artificial intelligence; Business metrics; Cellular; Cellular communication; Communications Engineering; Computer Communication Networks; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Connectionism. Neural networks; Cost control; Electrical Engineering; Energy; Energy consumption; Engineering; Equipments and installations; Evolutionary; Exact sciences and technology; IT in Business; Mobile radiocommunication systems; Network management systems; Networks; Optimization; Optimization algorithms; Quality of service; Quality of service architectures; Radiocommunications; Reduction; Software; Studies; Telecommunications; Telecommunications and information theory; Theoretical computing; Tuning; Wireless networks; Self-Optimizing Networks; Energy consumption; SON; Full frequency reuse; Multiobjective optimization; LTE-A; OFDMA; LTE; Evolutionary algorithm; Multiobjective programming; Frequency division multiple access; Downlink; Cell network; Power allocation; Optimization; Self organization; User service; Intercell interference; Metamodel; Mobile radiocommunication; MIMO system; Cellular radio; Maintenance; Neural network; Heuristic method; Orthogonal frequency division multiplexing; Wireless network
• ISSN: 1022-0038; 1572-8196
• DOI: 10.1007/s11276-013-0659-9

The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.