Reseach On Resource Allocation Strategy For A Mobile 5G Scenarios

At this stage,the exploration and construction of 5G mobile communication network technologies are rapidly progressing.The fourth-generation mobile communication system brings a variety of business services to users,especially mobile multimedia and online games,which require a large amount of data.However,with the continuous increase of the number of terminals in the future,users have more and more demand for seamless coverage services for mobile scenes,and put forward new requirements for 5G networks:(1)capable of achieving higher data transmission rates and larger networks.Capacity,less energy consumption and less time delay.(2)Provides seamless coverage services in poor channel state environments,especially for special scenarios such as high-speed mobile scenarios.Therefore,how to achieve a larger system capacity and less energy consumption in a mobile scenario,while providing accurate,slow,and efficient information transmission for users,becomes a fifth-generation wireless communication mobile scene.Research hotspots.This paper focuses on beamforming design and allocation of power resources and computing resources for reliability transmission and minimized delay in mobile scenarios.The third chapter of this paper proposes a centralized large-scale MIMO dual-slot cooperative multi-antenna vehicle communication transmission scenario.The research goal is to achieve the optimal total vehicle-to-vehicle communication speed when the train transmission power meets the constraints.The total system rate is continually iteratively optimized by adaptively adjusting the beamforming design of each time slot.The fourth chapter of this paper studies the optimization problem of distributed multi-antenna vehicle communication transmission system.Different from the third chapter,the fourth chapter considers the energy consumption limit of the backhaul link of the trackside base station.The research goal is to maximize the difference between the total transmission rate and the power consumption of the system.Finally,the distributed base station of the two time slots is solved.Beamforming matrix.Different from the high-speed driving scenario,the fifth chapter studies the video decoding task of mobile D2D users,which minimizes system energy consumption while ensuring user QoS.In the process of solving the problem,the problem model is transformed into a convex optimization problem by looking for the non-convex objective function and the substitution function of the constraint condition.Finally,the power and computation resources of the D2D user are calculated by the convex optimization tool.This paper combines the vision of 5G communication,analyzes and studies the resource allocation strategy in mobile scene,and analyzes and verifies the algorithm.The rationality and effectiveness of the proposed algorithm are proved by using MATLAB tools.This paper analyzes and studies the resource management algorithm in mobile scene,and analyzes and verifies the algorithm.The rationality and effectiveness of the proposed algorithm are proved by using MATLAB tools.