Resource Optimization Of Non-Orthogonal Multiple Access Network Based On Game Theory

With the rapid development of mobile communication technology and social technology,a number of new wireless network scenarios,such as self-driving car,intelligent agriculture,intelligent city and virtual reality,have been promoted.Massive wireless intelligent terminals are connected to the mobile communication network,which makes the existing wireless resources increasingly strained.Faced with scarce spectrum resources and limited network capacity,the NOMA network enables multiple users to share the same channel by superposition coding and successive interference cancellation technology,effectively improving spectrum usage efficiency and network capacity.Therefore,it is of great significance to study the network based on non-orthogonal multiple access technology.The main research content of this thesis is divided into the following two parts:(1)For the interference problem in a single-cell non-orthogonal multiple access heterogeneous network,the interference is mitigated by allocating subchannels and power resources in the network.The proposed resource optimization method models the network into a non-cooperative game model to maximize the interference pricing utility function as the optimization goal.The optimization method combines sub-channel allocation and power allocation.For the sub-channel allocation,a bilateral matching algorithm based on interference suppression is proposed.For power allocation,an iterative power allocation algorithm based on gradient descent method is proposed.The simulation results show that the proposed algorithm can improve the network capacity while taking into account the interference reduction.At the same time,NOMA network can achieve better network performance than the orthogonal frequency division multiple access network.(2)For the energy efficiency problems in multi-cell non-orthogonal multiple access heterogeneous networks,energy efficiency is maximized by allocating subchannels and power resources in the network.The proposed resource optimization method models the network into the Stackelberg game model,and maximizes energy efficiency as the optimization goal.The game model in the optimization method consists of two subgames,each of which also includes two parts:subchannel allocation and power allocation.For the subchannel allocation in the subgame,a bilateral matching algorithm aiming at maximizing energy efficiency is proposed.For the power allocation in the subgame,a power allocation algorithm based on Dinkelbach algorithm is proposed.The power distribution in the game can reach the equilibrium point of the Stackelberg game.The simulation results show that the proposed algorithm satisfies the user's service quality requirements and improves the network energy efficiency,which has strong practical value.