Research On Resource Allocation For NOMA In Heterogeneous Network

Non-Orthogonal Multiple Access(NOMA)technology realizes the multiplexing of user information by using the power domain.At the transmitting end,transmit multiple user information using the same spectrum resources through the active introduction of interference.At the transmitting end,the SIC technology is used to correctly decode user information to improve system throughput.Therefore,thesis focuses on the resource allocation for NOMA technology,the main work is as follows:Aiming at the problem of user association based on maximizing the capacity of NOMA system.The three-dimensional matching of users,base stations and sub-channels is an NP problem.Existing research decomposes three-dimensional matching into two-dimensional matching.In this thesis,an improved genetic algorithm is proposed to solve the multi-dimensional matching of users.Firstly,in order to meet the maximum total system capacity and reduce time complexity,the encoding method of genetic algorithm is designed as a multi-dimensional mapping process.Secondly,in order to increase the diversity and correlation between populations,the selection operator is deterministic and random combination.Finally,the best matching was obtained by crossing and mutation.The results show that the performance of the improved genetic algorithm is close to the exhaust algorithm and slightly better than the bilateral matching algorithm.Compared with the traditional genetic algorithm,it has the advantages of fast convergence.Aiming at the resource allocation problem based on the energy efficiency of NOMA system.The system energy efficiency is equal to the total throughput of the system to the total power consumption of the system.In order to obtain the overall energy efficiency,by established a mathematical model with energy efficiency as the objective function,the power allocation problem is decomposed into the power allocation problem of the users in the subchannel and the power allocation problem of the base station subchannel.For the power allocation problem of users in the subchannel,in order to ensure the quality of service of each user,a branch and bound algorithm is used to solve the problem,and in order to reduce the calculation complexity,DC planning is used to solve the sub-optimal power allocation.For the power allocation problem between sub-channels,iterative water injection algorithm is used to solve the problem.The power allocation algorithms within and between sub-channels are combined to optimize the energy efficiency of the system.