Research On Efficient And Energy-saving Resource Allocation For 5G

With the further development of Mobile Internet applications and the wide range popularization of massive intelligent terminals,new demands for various new services are thirsty to be met.The fifth generation(5G)mobile communication came into being in this situation.5G,which is a heterogeneous network of virtualization and densification,completely changes the existing cellular network architecture.In addition to the traditional wireless resources,there existing computing resources,storage resources,site and equipment resources and other types of resources in 5G network.How to improve resource utilization,enhance network utility and save energy cost while meeting the huge and diversified service demand by jointly allocating these resources flexibly and efficiently,is one of the current research hotspots of 5G network.Due to the uniform 5G network architecture and the diverse application scenarios,the resource types and optimization objectives are various,and the corresponding resource allocation objects are also different.Therefore,resource allocation schemes in different scenarios need to be studied separately.Based on above analysis,this thesis studies the resource allocation problem in some typical scenarios of 5G network.The main research contents are as follows:1)Research on an efficient wireless resource sharing scheme in sliced 5G radio access networkThe network utility maximization problem with dynamic resource allocation is studied in a sliced multi-tenant cloud radio access network(C-RAN).The fairness between users and tenants,the execution speed and the feasibility of the algorithm are considered in the problem formulation.In consideration of the hardness for solving the formulated problem directly,a distributed dynamic allocation algorithm is proposed to approximate the solution effectively.The algorithm can be divided into two steps:resource allocation inside the remote radio head(RRH)and the dynamic user association.A simple but efficienttwo-layer resource allocation scheme for the resource allocation sub-problem inside the RRH under the fixed user association is proposed,which improves the network utility while ensuring the fairness of tenants and users;For the sub-problem of dynamic user association,the unstable user is proposed innovatively,and a greedy algorithm of utility optimization is put forward,which can adjust the resource allocation and user association rapidly to achieve the dynamic optimization of the network utility when new users access the network or some users leave.Simulation results show the effectiveness for the method of resource allocation inside the RRH and the proposed dynamic user association scheme in which unstable users are focused.The proposed algorithm has a fast convergence speed and its performance close to the greedy algorithm which is high complexity.Thus it can be used for real-time dynamic resource allocation in multi-tenant sliced network.2)Joint Computation Offloading and Resource Allocation in C-RAN with Mobile Edge Computing(MEC)Considering the application of MEC in C-RAN,a novel task-aware MEC C-RAN structure is proposed.Then the problem aiming at maximizing the profit of network operator is taken into account,which jointly optimizes the offloading strategy,radio and computational resources allocation.After the description of network model,transmission model,calculation model and profit analysis of network operators,the optimization problem is formulated under the constraints of multiple resources and task delay.For the formulated problem is NP-hard,thus a spectral efficiency based joint optimization for offloading and resource allocation scheme is proposed.The original problem is decomposed into two sub-problems:offloading strategy designing and resource allocation.On one hand,after analyzing the optimization target and the users’offloading behavior,a spectral efficiency based offloading strategy is proposed;On the other hand,the sub-problem of computational resources and wireless resources allocation with a given offloading strategy is solved by a Lagrange multiplier method after some specific relaxing.Finally,by solving these two sub-problems iteratively,a suboptimal solution is obtained for the original problem.The simulation results show the effectiveness of the proposed algorithm,and the effects of delay constraint and task output size on the algorithm performance are also analyzed.3)Energy Saving Switching ON/OFF Strategies Analysis for Dense Cellular Networks with Partial Conventional Base-StationsWith the commercial use of 5G,a large number of 5G base stations have been deployed,thus new type base stations and conventional base stations are coexisting and densely deployed.Considering the situation that the conventional base stations are not suitable for switching on/off frequently,this thesis proposes a dynamic switching ON/OFF strategy to maximize the network energy efficiency.After applying a modified switching cost model,an Energy Efficiency Maximization Problem(EEMP)is formulated.The static EEMP with a constant user distribution is concentrated firstly,and four corresponding strategies are proposed.After that a Quality of Service(QoS)First Maximum Energy Efficiency(QFMEE)algorithm is proposed with consideration of the switching cost,in which the users’QoS are satisfied preferentially.Firstly,the best static EEMP strategy is selected based on the simulations,and then the simulation analysis for QFMEE is carried out.The conclusion is that the QFMEE scheme can improve the network energy efficiency and reduce the switching cost significantly when the switching cost occupies a considerable proportion in the total energy consumption.