User Association Algorithm Based On Energy Efficiency Under Ultra-dense Deployment

With the widespread use of user terminals such as smart phones and tablet computers,data traffic and mobile services have experienced an explosive growth trend.In 2020,mobile communication systems will face enormous challenges.Although 4G technology has greatly improved the network capacity and user data rate compared to 3G,it still cannot meet the increasing traffic demand.In order to meet the communication requirements of low energy consumption,high capacity,and low latency,5G standards and technologies has become a hot spot in current research.Ultra-Dense Network(UDN)technology has become an inevitable trend in the development of mobile communications as one of the key technologies in 5G.Ultra-dense deployment is realized by increasing the density of small cell base stations under the coverage of macro base stations to achieve ultra-dense deployment of base stations.The increase of traffic demand and the number of base stations will inevitably lead to a large consumption of base station power.How to reduce the energy consumption of the base station and realize the “green cellular network” is the future goal of the mobile network.A suitable user association algorithm has important implications for reducing system energy consumption.Based on this,this paper will further study the algorithm of user association under ultra-dense deployment,in order to further improve the energy consumption of the system.This paper studies the user association algorithms considering energy efficiency and energy consumption in ultra-dense deployment heterogeneous networks.Firstly,taking the system energy efficiency as the optimization goal and combining with the cell sleeping,a user association algorithm based on cell sleeping is designed to improve the original throughput-based algorithm.Secondly,considering the ultra-dense network of renewable energy and grid energy supply at the same time,a green energy-aware user association algorithm is designed.The main contents and innovations of this article are as follows:(1)The first part of the work takes the system energy efficiency as the optimization goal,and the user association algorithm based on cell sleeping is designed.In the process of user association,both the throughput obtained and the energy consumption of the base station are taken into consideration,and submit the access request to the base station providing the maximum energy efficiency.After the user association process is completed,different from the sleep of the no-load cell of the original algorithm,the algorithm of this paper will consider making some light-load small cells satisfying the conditions a sleeping cell,and give a decision criterion of whether the light-loaded base station can become a sleeping cell.Finally,the algorithm of this paper and the comparison algorithm are simulated.The simulation results show that the algorithm guarantees the throughput,and it is superior to the comparison algorithm in energy consumption and energy efficiency of the system,and meets the requirement of “green communication”.(2)Unlike the traditional single-grid energy supply network,this paper considers a network which is supplied with both grid energy and renewable energy at the same time,and designs a green energy-aware user association algorithm which users can adaptively adjust the associated strategy based on the power consumption of the base station and the green energy usage.The algorithm improves the traditional matching theory based on the maximum SINR.The utility function is designed according to the green energy and the base station energy consumption,and the different priorities of the base station is set according to the remaining situation of green energy.Finally,combined with the resource optimization algorithm to complete the user access process.The diversity of base stations and the ultra-dense deployment of base stations have changed the link conditions and interference conditions in the network.To more accurately capture the path loss between the base station and the user,this part of the algorithm uses a dual-slope path loss model architecture.The simulation results show that the power consumption of the system and the power consumption of the macro base station are significantly reduced when the data rate requirement of the user is satisfied,and the energy efficiency and the load balancing index of the algorithm is also better than that of the comparison algorithm.