Research On Resource Allocation Of Wireless System Based On Bilateral Stochastic

With the increasing number of personal wireless devices and the rapid development of Internet of Things technology,Fifth Generation(5G)mobile communication systems will face the problem of explosive growth of data traffic,which will lead to a sharp increase in the cost of energy in the communication system.In order to reduce the Energy cost in 5G network,it is an effective solution to equip the base stations with Renewable Energy(RE)capacity equipment.At the same time,thanks to the development of smart grid technology,communication operators have more choices in their energy decisions.However,Re productivity and base station user access are stochastic in time,so how to allocate resources in the communication system has become an urgent problem to be solved.To this end,this thesis proposes a communication side and supply side bilateral communication system model of random,comprehensively consider the randomness of communication side user demand and supply side of new energy capacity of randomness,through a user scheduling,beam informs and the base station energy decision-making method to reduce the energy cost,improve the system performance and achieve green communication.Firstly,based on the randomness of user distribution and the randomness of base station’s energy supply,a two-sided stochastic system model of communication side and power supply side is established,and the relationship between base station’s energy consumption and energy procurement cost is analyzed.Secondly,a two-sided stochastic model of user allocation and energy decision is designed by combining the two models,and a hybrid energy supply algorithm based on matching game and convex optimization is proposed.On the basis of guaranteeing the Quality of Service(Qo S),the algorithm minimizes the cost of purchasing energy by optimizing the scheduling of users and the decision of purchasing power of base stations.Simulation results show that the proposed algorithm can effectively reduce the energy cost of the system.Finally,considering the uncertainty of RE productivity,a resource-constrained multi-user multi-base heterogeneous network model is constructed.To maximize the sum of SNR of users in the system,a hybrid optimization algorithm composed of linear programming and multi-objective optimization is proposed.The simulation results show that the algorithm improves the system performance by optimizing user scheduling and beam shaping after comparing the existing stock of RE generating energy and energy storage equipment in the base station.