Resource Allocation Algorithm Based On Alliance Game In Ultra-Dense Networks

With the rapid development of modern mobile communication technology,China's 5th generation mobile networks(5G)technology has achieved full commercial use now.It meets the needs of the growing business volume and smart terminal connection in the mobile communication industry,and satisfies higher communication service quality,more convenient communication methods,faster communication speeds and lower communication costs and other requirements in the market.Facing the explosive growth of communication traffic and smart terminal connections,the 10-fold increase in spectral efficiency brought by improving coding,modulation,and multipleaccess technologies is far from enough.Therefore,one of the 5G core technologies named "ultradense networking technology" is the key to solving the problem.Pico base stations and Femto base stations deployed in ultra-dense network structures are flexible sites with low transmit power and small coverage area.This dense deployment of lowpower nodes is indeed the best solution to achieve ultra-high traffic and ultra-high user access,but it also brings many problems that cannot be ignored.The sharp increase in the number of base stations not only brings management troubles,the increase in base station power consumption,and the same-layer and cross-layer interference in different frequency bands have seriously affected the communication quality.Resource issues such as interference and power have restricted the further development of ultra-dense networking and even 5G communication technologies.In order to solve the interference and power consumption problems caused by the increase in the number of base stations in ultra-dense networking,this article analyzes the correspondence and contradictions between base stations and users to build a network model for ultra-dense networking.In this paper,a joint interference power optimization resource allocation algorithm based on alliance game is designed,and relevant simulations are performed to prove the advantages of the proposed algorithm.The main research contents are as follows:First,in order to solve the significant increase in power and interference caused by the increase of base stations and users,the power consumption-based alliance resource allocation algorithm and interference-based alliance optimization algorithm(PFRA-AG algorithm and IFRA-AG algorithm)are proposed.The mapping relationship of the alliance game is established in the system model,and the co-layer interference of the individual users or the power consumption of the base station is calculated as the optimized decision utility function to implement the iterative update of the particle swarm optimization of the network structure.The simulation results show that the PFRA-AG algorithm and the IFRA-AG algorithm can significantly improve the throughput of the system.However,due to the choice of non-cooperative games,they can reduce the power consumption(interference)while the interference(power consumption)will be obviously rise.Second,based on the upgrade of the PFRA-AG algorithm and the IFRA-AG algorithm,this paper proposes a resource allocation algorithm(RAIP-UN algorithm)based on joint optimization of interference power consumption.In this algorithm,the improvement of the alliance decision threshold becomes the joint effect function of interference power consumption,and the system reliability guarantee algorithm based on the sleep wakeup of the base station is used to constrain the iterative loop of the overlapping alliance.By analyzing the problems of power consumption and interference in the same layer within the alliance,unearth the connection and contradiction between interference and power consumption,and then using the idea of alliance game to weigh the utility functions,to obtain an optimal network structure of Nash equilibrium.Simulation experiments show that the RAIP-UN algorithm achieves synchronous optimization of interference power consumption of individual alliances in the system,and the system throughput is significantly improved.The efficiency is higher than PFRA-AG algorithm and IFRA-AG algorithm.