Research On Base Station Energy Saving Strategy Oriented Toward Multi-Service User Experience

With the development of wireless communication technologies and the popularization of intelligent mobile communication terminals,5G networks are developing toward large-scale ultra-dense networking,and the high energy consumption and carbon emissions problems brought about by them have received extensive attention.Energy saving for base station networks has become a hot research issue in the field of communications.Utilizing the tidal phenomenon of base station traffic in the city and the unbalanced traffic load of base stations in different areas of the space,shutting down some underutilized base stations properly and offloading the traffic to their neighbors on the premise of guaranteeing the user experience can effectively reduce the energy consumption of the mobile communication networks.The main content of this paper is as follows:1.The existing strategies mainly focus on Quality of Service for users,while not fully considering the influence of user experience for specific applications.Aiming at this,this paper proposes a base station Energy Saving strategy oriented toward Multi-Service User Experience(ES-MSUE),utilizing Quality of Experience as a metric for the user's subjective experience.Specific utility functions are used to model the multi-service user experience as different transmission contents has different characteristics.2.Nonlinear integer programming is utilized to model the energy saving problem,Specifically,this paper converts the multi-objective optimization of base station energy consumption and multi-service user experience into a joint optimization goal,nonlinear integer programming is utilized to model the above problem.By adjusting coefficient in the object function we can get the trade-off of the network energy consumption and user experience.3.At the same time,in order to solve the problem of high complexity brought by large-scale base stations,this paper uses complex networks to model to the affinity of base stations according to the proximity and cooperation relationship of base stations,divided them into multiple communities by community detection method,and achieves parallel implementation of the ES-MSUE.4.Experiments based on the real UDRs of mobile users from urban areas of Jinhua has been conducted,and by comparing with other relative energy saving strategy,the results show that ES-MSUE achieves better performance on user experience and energy savings.And the parallel implementation scheme greatly improves the calculation efficiency of the energy-saving strategy under the condition of ensuring the energy-saving and user experience,which shows strong implementation possibilities in large-scale base station clusters.ES-MSUE proposed in this paper achieves good energy-saving and user experience,and the parallel implementation scheme based on community detection makes it applicable to the energy saving of large-scale urban cellular networks,and has certain reference value for the actual base station energy-saving strategy.