Cross-Layer Power Allocation Scheme And Multi-Objective Joint Optimization Design In NOMA Systems For 5G

Non-Orthogonal Multiple Access(NOMA)is one of the key technologies of 5G.By using superposition coding and successive interference cancellation in the NOMA system,multiple users with different power can be served in the same time-frequency resource block.Hence the capacity of the system is greatly increased.Resource allocation is an important factor for affectting the performance of NOMA system.In order to satisfy the complex and severe requirements of network in 5G enviroments,the optimization scheme of resource allocation is studied,considering the Sum Rate of system,Fairness Index,Quality of Service(Qo S),Energy Efficiency and Spectrum Efficiency.The main work of this thesis can be summarized as follows:Firstly,from the perspective of ensuring user's Qo S,based on cooperative communication system with the optimation goal of maximizing the minimum effective capacity,a cross-layer power allocation algorithm,combining the penalty function method and improved simulated annealing algorithm,is proposed in this thesis.By using penalty function method,the original constrained optimization problem of maximizing the minimum effective capacity is transformed into unconstrained optimization problem.Then the simulated annealing algorithm is used to obtain the optimal power allocation scheme.The simulation is carried out in the scenario of two users and multiple users for half/full-duplex cooperative NOMA.The simulation results show that the proposed algorithm can further increase the effective capacity of the NOMA system comparing with the existing power allocation algorithm.The proposed algorithm can also get the same optimal solution of exhaustive search with faster convergence speed.It can be used as a cross-layer power allocation scheme for compromising algorithm complexity and increasing effective capacity.Secondly,a multi-objective joint optimization in the downlink of Multiple Input Single Output NOMA(MISO-NOMA)is studied to satisfy the complex requirement of 5G network.An SE-EE joint optimization scheme is proposed considering the energy efficiency and spectrum efficiency.And an SR-FI joint optimization scheme is proposed considering the sum rate and fairness.The multiobjective optimization problems in the proposed schemes turn into single-objective optimization by using the weighted sum function.The original non-convex optimization is approximated by a convex optimization using the sequential convex approximation.Then the pareto optimal solution is iteratively obtained.The simulation results show that the two proposed joint optimization schemes can bring more flexibility to the base station for resource allocation.The base station can flexibly adjust the weighting factor in according to the actual application scenarios,so as to meet different performance requirements in various scenarios.