Research On Key Technologies Of Traffic Offloading Strategy For Heterogeneous Cellular Networks In Smart Grid

With the development of smart grids,power grid operations require strong support from power communication networks.There are many smart devices in the power communication network,and the amount of data transmission has increased rapidly.It is difficult for existing smart grids to meet this demand.As a more flexible network architecture model in the smart grid,heterogeneous cellular networks can effectively increase the capacity of the cellular network and meet the data traffic requirements of the smart grid user-side devices.However,it is difficult to incentivize micro cells to participate in traffic offloading and intelligent offloading of user-side devices in heterogeneous cellular networks.Therefore,in order to increase the network communication quality,this paper studies the traffic offloading incentive mechanism and traffic offloading method in the heterogeneous cellular networks.The main contributions of this dissertation are organized as following:1.Aiming at the problem of information asymmetry in heterogeneous cellular network of smart grid,this paper proposes a design method of incentive mechanism for traffic offloading based on contract theory.First,the contract theory is introduced into the heterogeneous cellular network to construct macro base station and femto base station models.Secondly,for the problem of adverse selection caused by the femto base station's participation in the traffic offloading process,we design individual rational constraints to ensure that the femto base station participates in the traffic offloading process to obtain non-negative utility and incentive compatible constraints to ensure that the femto base station participates in the traffic offloading process can obtain maximum utility when selecting contract items related to their private information.Then,a contract optimization problem based on the effectiveness of the macro base station is designed,and the utility type of the macro base station is optimized by identifying the true type of the femto base station.Finally,the experimental results show that the contract incentive mechanism proposed in this paper can motivate femto base stations to efficiently participate in traffic offloading tasks.2.Heterogeneous cellular networks can balance traffic loads and reduce cell arrangement costs,which is an important technology of future mobile video communication networks.Because of the characteristics of non-convexity of the mobile offloading problem,the design of the optimal strategy is an essential issue.For the sake of ensuring the service quality of the smart grid user-side power grid equipment and the long-term overall network utility,this article proposes the distributive optimal method by means of multiple agent reinforcement learning in the downlink heterogeneous cellular networks.In addition,to solve the computational load issue generated by the large action space,deep reinforcement learning is introduced to gain the optimal policy.The learning policy can provide a near-optimal solution efficiently with a fast convergence speed.Simulation results show that the proposed approach is more efficient at improving the performance than the Q-learning method.