The Research On Deployment Startegy And Energy Saving Mechanism Of Heterogeneous Cellular Network

In recent years, people pay more and more attention to power consumption and environmental problems and these problems have been frequently mentioned in. international affairs. With the rapid rise of smart phones and the application of 4G technology, information and communication industry usher in explosive growth. The resulting energy consumption and CO2 emissions issues have reached the point that cannot be ignored. According to statistics, the power consumption of the communications industry has accounted for a huge percentage of total global energy consumption and it is rapidly increasing year by year. In order to solve the problem of power, scholars put forward many new technologies to improve energy efficiency. Heterogeneous cellular network has received widespread attention in academia. The so-called heterogeneous is to introduce a variety of low power nodes to traditional isomorphism cellular network, which are collectively referred to as micro base station. Micro cells can share traffic with macro cells in hot spots region for traffic load balancing so that they can improve system capacity and energy efficiency. At the same time, the micro cells can serve the users which are at the coverage edge of macro cells with high speed and high quality service.At present, there has been a lot of researches on the cellular system for heterogeneous, but most of them only take the base stations power consumption into consideration while ignoring the power consumption of the mobile terminals. In this article, we will put forward a comprehensive base station deployment strategy which is based on energy efficiency and take the power consumption of base stations and mobile terminals both into consideration. We apply the Monte-Carlo model to simulation and modeling. Micro cells are added to the edge of the traditional macro cells and different and more accurate power consumption models are used to analyze the characteristics of macro cells and micro cells. At the same time, we introduce the business simulation to make the micro cells and mobile terminal power consumption is associated with real-time dynamic load. In others words, the energy consumption will be divided into static part and dynamic part. Through the simulation we find that whether to increase the number of micro cells or expanding radius of micro cells can improve the system efficiency. Of course, the radius of base station shall be restricted in a certain range to conform to the characteristics of low power node. Thus, we can get the optimized number and radius of micro cells and the highest energy efficiency of the system. In this deployment strategy, our dormancy of the original algorithm is improved. Different strategies of dormancy are applied for micro cells and macro cells.Distributed architecture is adopted and we use voting to get local optimal dormancy strategies. The simulation results show that the improved dormancy algorithm has lower system power consumption.