Research On User Association And Power Allocation Strategies In Heterogeneous Cloud Access Networks

To support the rapidly increasing requirements for mobile multimedia service and to satisfy the objectives of high energy efficiency and high spectrum efficiency,the heterogeneous cloud access network(H-CRAN)has been proposed.How to reduce energy consumption and achieve energy saving under the premise of ensuring service quality and user data rate is one of the hot topics in heterogeneous cloud access networks.This dissertation studies energy-efficient user association and resource allocation strategies in heterogeneous cloud access networks.Firstly,the strategies of user association and power allocation for heterogeneous cloud access network using hybrid energy are studied.Then this paper studies the joint sleep,user association and power allocation strategy and analyzes the corresponding performance.The main research contents and contributions of the dissertation are summarized as follows:1.User association and power allocation strategy for hybrid energy supplyRegarding the heterogeneous cloud access network using hybrid energy,an energy-saving user association and power allocation strategy is studied.Firstly,remote radio heads(RRHs)are partially empowered by renewable energy sources and the others are empowered by grid power.Then,to optimize the power consumption of the grid,the problem of optimizing the user association and power distribution is modeled as a mixed integer programming problem with constraints in the user data rate and the renewable energy.In order to facilitate the solution of the problem,the problem is transformed from optimizing the power consumption of the grid to optimizing throughput of RRHs empowered by renewable sources.And then using Lagrange dual decomposition method to solve the optimization problems.Finally,the simulation results verify the effectiveness of the proposed algorithm and its performance advantages in energy saving.2.Energy-efficient user association and power distribution strategy with limited fronthaul capacityIn H-CRAN,not only the transmit power consumption but also the fronthaul power consumption and static circuit power consumption should be considered,therefore,the power savings can be achieved by switching off some RRHs.Regarding the influence of node selection on network energy efficiency in H-CRAN with limited fronthaul capacity,an energy efficient approach combined RRH selection,user association,and power allocation is studied.To maximize the network energy efficiency,the problem of optimizing RRH selection,user association and power distribution is modeled as a mixed integer programming problem with constraints in the user data rate,the wireless fronthaul link capacity and the transmission power.The intelligent evolutionary algorithm with hybrid fitness function is used to solve the problem,and an energy efficient joint RRH selection,user association and power allocation algorithm is proposed.The simulation results show the advantages of the proposed algorithm in improving network energy efficiency.