Research On Energy Efficiency Optimization Of Hybrid Energy Supply Heterogeneous Network

In recent years,with the transformation of the global information industry and the rapid development of wireless communication technology,mobile terminal devices and data traffic have shown explosive growth,and the rise of various new network architectures and new technologies has increasingly increased the performance demand for communication networks.In order to meet the communication service requirements of multiple users and improve system capacity and coverage,heterogeneous networks have emerged as the times require.Heterogeneous networks are composed of multiple power type base stations and related communication devices,while supporting flexible access to multiple network types,improving the flexibility and stability of network communication,and providing highquality and diverse communication services for end users.However,the intensive deployment of base stations with different power types in heterogeneous networks can lead to increased overall system energy consumption and interference.The energy consumption cost of base stations is an important issue that operators need to address.In order to alleviate the energy consumption problem of the base station,two schemes,open source and throttling,have been introduced to reduce the energy consumption of the base station.The open-source solution introduces renewable energy and utilizes energy collection technology to power base stations,reducing their energy consumption on the power grid.On the other hand,throttling schemes include power allocation technology and energy collaboration technology.Efficient power allocation technology can improve the communication quality of the network and effectively reduce base station power consumption.Energy collaboration technology shares surplus renewable energy with other foundations through intelligent network architecture.The dual-layered heterogeneous network and the Internet of Things,as two important sub-architectures in heterogeneous networks,are the main research objects of this article.The specific research content is as follows:(1)This paper studies the resource allocation problem of hybrid two-layer heterogeneous network with the goal of maximizing energy efficiency.First of all,considering the quality of service constraints of users and the transmission power constraints of base stations,the downlink transmission model of hybrid energy supply network is considered,and the resource allocation optimization problem to maximize energy efficiency is proposed.Considering that the problem is a nonlinear programming problem with multivariable coupling,the fixed variable method is used to reduce the problem into sub-problems of user association,power allocation and energy cooperation,On this basis,Lagrange dual method,improved particle swarm optimization method and matching algorithm are used to solve each sub-problem.The simulation results show that the above joint iteration scheme has good convergence and energy efficiency performance,and also proves that the energy collection technology and energy cooperation technology can effectively improve the overall energy efficiency of the system.(2)The resource optimization problem for supporting the(Wireless Information and Power Transfer,SWIPT)Internet of Things under hybrid energy supply is studied,with the goal of maximizing energy efficiency.To extend the network operation time of wireless terminal equipment,SWIPT technology is used to provide communication services and energy supply for wireless terminals.Firstly,considering the constraints of base station transmission power and time handover coefficient,an energy efficiency optimized resource allocation problem is proposed for the downlink transmission model of the Internet of Things.Due to the coupling relationship of multiple variables,the optimization problem is a nonlinear programming problem that is difficult to solve directly.Therefore,a two-level iterative solution is proposed.Firstly,the fixed variable method is used to decompose the problem into three sub-problems: success rate allocation,time switching,and energy collaboration.For power allocation and time switching,the Dinkelbach method is used to solve them.Then,a matching algorithm is used to solve the energy collaboration problem.Finally,simulation results verify the convergence and effectiveness of the proposed scheme.It is verified that the scheme has good performance in different situations.