Research On Technology Of Ultra-dense Network With NOMA

Ultra-dense network(UDN)through the dense deployment of a large number of low-power wireless access points(APs),it has become a typical application scenario for the fifth generation mobile communication system(5G)to improve spectral efficiency.Non-orthogonal multiple access(NOMA)technology improves system throughput through non-orthogonal transmission in the power domain or code domain,it has become one of the promising transmission methods for 5G.The effective combination of UDN and NOMA is the research focus of scholars in recent years and it is also the focus of this paper.The research in this paper conducts research from the following three aspects:(1)First,the paper focuses the research on how to effectively increase system throughput.In the previous selective clustering study,the clustering of APs and the adjustment of transmission power were divided into two steps.Although this reduces the complexity of the algorithm,it comes at the expense of system performance.This paper combines the simulated annealing algorithm with selective clustering for users and APs,and proposes a single-objective optimization algorithm,which performs the clustering between APs and the transmission power allocation process simultaneously.According to the actual needs of the scene,this paper gives the specific steps of the optimization algorithm.Through the analysis of the simulation results,the algorithm proposed in this paper changes the original clustering method,when the selected AP can bring better communication services to the user even if the AP is not around the user.And AP can be connected to users to provide data transmission services,ensuring fairness in the clustering process.Compared with the previous clustering algorithm,the optimization algorithm proposed in this paper effectively improves the system throughput and obtains a gain of approximately 10%.The maximum number of APs that can provide services to users,Q,is studied.When the number of APs in a unit area is large,the larger the value of Q,the more obvious the gain in system throughput.(2)Based on the NOMA theory,this paper studies the reliability of the receiver and an improved design of the successive interference cancellation(SIC)receiver is carried out.Firstly,this paper analyzes the mathematical model and working mode of the traditional SIC receiver,points out its error transmission and other phenomena,and the blind source separation(BSS)technology is used to improve the design of the receiver.The independent component analysis(ICA)method is used to separate the blind signal,and required signal is estimated in advance in the mixed signal.The useful signal is compared with the signal in the subsequent decoding process,which effectively eliminates the interference between the signals.By comparing the performance of traditional receivers,the receiver designed in this paper can effectively suppress the impact of bit error transmission on signal demodulation,reducing the bit error rate(BER)of the signal.(3)Finally,based on elitist non-dominated sorting genetic algorithm(NSGA-?),the paper has proposed a dual-objective optimization algorithm to consider the balance between performance indicators of actual communication scenarios.Taking the average user rate and system energy efficiency as the optimization goals of the algorithm,the simulated binary crossover(SBX)method is used to perform crossover operation on the population,and the optimal frontier solution of the system is obtained in scenarios with different numbers of users and Q values.When the number of people is constant and the Q value is large,the decrease in the average rate of users cannot bring a more obvious gain in system energy efficiency.When the Q value is constant and the number of people is small,the energy efficiency of the system can be increased by sacrificing the average rate of users.