Research On Resource Allocation And Precoding Scheme In High Rate Wireless Communication

With the development of wireless communication and Internet of Things technologies,end-users have presented an explosive growth,and wireless communication systems have also begun to develop towards the direction of isomerization,ultra-denseness,and edge intelligence.In the future,wireless communication will also have the characteristics such as ultra-high connections and ultra-high speed,which will bring huge challenges to the design and deployment of wireless communication systems.The power-domain non-orthogonal multiple access technology can realize the access of a large number of end-users and improve the spectrum efficiency.However,it is very difficult to accurately obtain real-time channel state information in practice.Therefore,it is necessary to conduct in-depth research on the performance analysis and optimization methods of the statistical channel NOMA system.Future wireless communications require new effective paradigms that have both spectrum efficiency and energy efficiency.Terahertz communication is considered to be a promising technology,but due to its bandwidth characteristics,the path components are split into completely separate spatial directions at different sub-carrier frequencies.This causes the existing high-energy-efficiency hybrid precoding schemes unable to be directly applied to terahertz communication,therefore,it is necessary to conduct in-depth research on broadband hybrid precoding schemes.The specific research work is as follows:(1)In the statistical channel downlink NOMA system,aiming at the problem that the maximization of system sum rate cannot be solved directly,a step-by-step resource allocation optimization scheme based on machine learning is proposed.First,in order to achieve a trade-off between the system sum rate and user fairness,the system throughput formula is derived.Then,according to the combined characteristics of the system throughput maximization problem,it is divided into two sub-problems,that is power allocation and user grouping.Finally,the problem is solved in two stages.In the first stage,based on any pairwise grouping of users,an improved genetic algorithm is used to allocate power to maximize intra-group throughput within each group.In the second stage,based on the results of the first stage,the Hungarian algorithm is used to determine the user grouping set that maximizes the system throughput.By comparing the ergodic rate of NOMA users with statistical CSI and perfect CSI,the effectiveness of the statistical CSI sorting process is verified.Compared with the traditional orthogonal multiple access scheme,the NOMA scheme which uses random user scheduling and fixed user scheduling,the system throughput performance of the proposed scheme is significantly improved.(2)In terahertz downlink communication system with traditional hybrid precoding structure,a wideband hybrid precoding scheme based on cyclic delay is proposed to solved the beam diffusion problem.First,construct a hybrid precoding framework based on cyclic delay.A delay unit is placed on each antenna of the traditional fully connected hybrid precoding structure,and a frequency-dependent phase shift is introduced to compensate for beam diffusion.Then,by maximizing the array gain of the sub-carriers,the unit delay amount of the delay unit on each antenna is determined,but there is a problem that the unit delay amount is not uniform.Finally,through the design of analog precoding,the unit delay amount of the delay unit on each antenna is unified while ensuring the maximization of the array gain of each sub-carrier.The simulation results show that the proposed scheme can achieve 100%array gain at any sub-carrier,and is adapted to solve the beam diffusion problem under different bandwidths and different numbers of transmitting antennas.Compared with the existing scheme,the achievable rate of the proposed scheme is very close to that of the all-digital precoding scheme,and has the advantage of high energy efficiency.