A Study Of High Energy Efficiency Joint Resource Allocation Algorithm For LTE System

As the increasing reduction in renewable energy and growingly serious global warming issue, energy saving and emission reduction has become a worldwide topic. According to statistics, the current ICT industry energy consumption accounts for about 2% to 6% of the world’s energy consumption, and the proportion is increasing rapidly. It has been a long story about the high energy consumption in communication industry, especially the rapid development of cellular mobile communication makes the problem become more prominent.In view of this problem, green communication historic became the new task of the communications industry. Green communication is not simply to reduce the energy consumption for the first goal, but to minimize the energy consumption, reduce environmental pollution and greenhouse gas emissions on the premise of meeting users’ business requirements under the limited communication resources.For this task in LTE system, radio resource management based on green efficiency has become an important means of solving this problem. The business types and Qo S needs of LTE system are more diverse, but it is impractical to meet the different business needs unlimitedly or to meet the harsh business needs by wasting a great of resources. Under the condition of meeting different users’ demands, how to efficiently and reasonably allocate the radio resource has become the hot topics in the study of LTE system. Radio resource management should not only guarantee the system throughput, energy efficiency and user fairness, as well as the complexity and convergence of the algorithm also has the corresponding requirements.In this paper, from the start of original meaning of efficiency, analyzing the connotation, extension and optimizing criterion of the wireless communication, I convert the problem into a accurate descripted, formulation defined rigorous theory model by mathematical language. For LTE network, this paper constructs a utility function by the theory of green efficiency and diminishing marginal effect, and this paper aims to achieve the joint resources optimization by this utility function. Based on the high computational complexity of multi-dimensional resource joint optimization algorithm,this paper introduces a way of distributed search and iterative optimization to approximate Nash bargaining solution in order to guarantee the real-time performance. The basic particle swarm optimization(pso) algorithm is a heuristic evolutionary algorithm, the basic idea is the result of the birds, fish and other creatures in the nature colony foraging behavior simulation research. Though it has a simple parameter setting and a fast convergence speed, it is easy to fall into local optimum to get a low quality global optimum. For the flaws in the basic pso algorithm, I introduce a combined model pso algorithm to adjust global optimization ability and local optimization ability adaptively. And the proposed algorithm can avoid falling into local optimum and improve its optimization ability on the basis of ensuring the convergence rate of the step-by-step search. Finally, I have built the platform and simulated the proposed algorithm by Matlab. I have compared the performance with the traditional resource management algorithm and verified the superiority of the proposed algorithm.