Traffic Based Energy Saving Model And Mechanism In Wireless Access Network

Green Telecommunication has become a key subject in recent years. The energy consumed by system and devices in wireless communication network, as well as carbon emission, accounts for a large portion of that in Information of Communication Technology, and there’s a trend of increase. Since access nodes such as base stations, are widely deployed in wireless access network, their energy consumption takes about60%of total energy consumption in wireless communication network, and this figure is increasing with the deployment of the fourth generation mobile telecommunication system. Thus energy saving of base stations is the key to green wireless communication network.In order to maintain quality of service in wireless communication systems, the capacity are designed to meet the demands of peak time traffic. However, when service applications are quite fewer, base station capacity utilization is quite low, which is waste of capacity resource and energy resource. Thus closing a number of base stations during low traffic period is one of the most efficient ways of energy saving in wireless access network. However the energy model used in recent researches did not considered the dynamic energy consumption, which is related with base station coverage and capacity, and some of the energy saving mechanisms are either not efficient enough, or brings much impact on network quality.For UMTS network scenarios, we propose a traffic-based centralized automatic energy saving mechanism. Firstly, the mechanism gives the energy consumption model which is related with traffic load. Then the mechanism divides an operating period of base station into several phases, different energy saving operations is executed on different phases. The mechanism provides several consumption methods for the closed base stations, and the way to get the most appropriate compensation combination according to the traffic and location of the closed base station. Furthermore, we proposed the energy saving trigger algorithm which is executed during traffic decrease, and the energy saving recover algorithm which is executed during traffic increase. The two algorithms take the leverage between energy saving and quality of service. Finally we describe the evaluation model for energy saving, and evaluate the efficiency of our centralized mechanism in UMTS simulation scenarios. For LTE network scenarios, we propose a traffic-based distributed automatic energy saving mechanism. We proposed a much steady operating period division and the selection method of compensation combinations of closed base stations according to feature of distributed mechanisms. After that, the mechanism describes the metric for compensation combination ranking. Then we proposed our distributed the energy saving trigger algorithm and the energy saving recover algorithm. Finally we evaluated the efficiency of our distributed mechanism in UMTS simulation scenarios...