An Evolutionary Approach for Resource Allocation in LTE-Advanced Cellular Network

During the last decade, there has been tremendous growth in cellular networks market. The number of subscribers and the demand for cellular traffic has escalated astronomically. Such unprecedented growth in cellular industry has pushed the limits of energy consumption in wireless networks. Furthermore, base stations (BSs) consume more than 50 percent of the power of a cellular network. Thus, reducing
the power consumption of BSs is crucial to green cellular networks. In LTE-Advanced cellular networks, a BS may transmit signal on multiple component carriers (CCs) with different power. In this work, we consider the problem that finding a nearly optimal CC selection pattern for all BSs which could satisfy all of the QoS constraints of UEs with minimum power consumption of BSs. We will show that it could
be formulated as a mixed integer nonlinear programming (MINLP) optimization problem which is always hard to solve. Combining the concepts of interior point method and particle swarm optimization, we propose a novel method for solving our problem. Simulation results show that the solution solved by proposed method is not only nearly optimal but consumes less power than the compared method.