Resource Management Of 5G Mobile Communication Network Based On The Energy Efficiency

3G and 4G enable the development of mobile communication networks to be full of vitality. The mobile Internet and IOT as the two driving forces of the mobile communication demand a higher device access density and mobile data traffic. The development trend of the future 5G communications networks is that adopts the high density heterogeneous cellular network infrastructure to meet the growing user’s access density and high data rate requirements. At present, the energy consumption of mobile communication industry accounts for 3% of total energy consumption globally which is much higher than other industries, and the energy consumption of base stations is about60% to 80%. The future high-density overlapping heterogeneous cellular network architecture means deploying more base stations and these deployments are more random which is no doubt to bring more serious challenges to the energy consumption of the mobile communication network.In this paper, we propose a research method to improve network efficiency of resource management under a high density heterogeneous network architecture which consists of the Macro cell, Micro cell and small cell. The research mainly includes two parts: in the paper by the Macro cell, Micro cell and small cell three network consisting of high density under heterogeneous network architecture, research method to improve network efficiency of resource management, mainly includes two parts:(1) We propose a user access selection algorithm based on a comprehensive cost function to enable users to connect to a appropriate network in the high-density overlapping coverage network. Traditional access algorithm is that the user accesses to the base directly which the signal perceived by the user is strongest, but the signal intensity that the user receives from the macro cell base station was significantly stronger than the micro and small cell base station under the 3GPP channel model and the default deployment parameters which makes congestion and poor user experience on part of the base stations due to connect excessive users and on the other hand wastes network resources because most of the small cell base stations are vacant. The proposed algorithm has a better load balancing performance which can improve system capacity and lower offline rate.(2) We propose a power control algorithm based on energy efficiency whichcombines cell breathing technology and base station sleeping technology, aimed at improving network efficiency by reducing the energy consumption of base stations under the premise of ensuring the communication quality. In the algorithm, each base station is divided into zero load, light load, normal load and heavy load operation state based on the load state, and then adjusts its transmit power according to the operating state, so as to change the coverage area of the base station.Two algorithms are complementary and interactive: the user access selection algorithm determines user’s access according to the operating state of base stations and the distribution of users, and the power control algorithm adjusts the working status of each base station according to load status which is determined by the numbers of access users, then gives feedback to the access selection algorithm part. In a variety of simulation scenarios, the simulation results show that this resource management algorithm can improve the energy efficiency of the network by 15% to 65% in the sparse uniformly distribution, single-point dense distribution and multi-point intensive distribution which benefits from the system capacity has a significant upgrade and power consumption is significantly reduced. In the dense uniformly distribution scene,the energy efficiency has a small decline since the power consumption becomes larger,but the communication quality is enhanced because the capacity of system improves significantly, while the dropping rate is the lowest of all algorithms.