Research On Energy Efficiency Optimization Of Terahertz MIMO-NOMA System Assisted By SWIPT

Frequency resources in terahertz bands are extremely rich,but there is a significant path loss,so it is often integrated with Multiple-input Multiple-output(MIMO)technology,which provides a large spatial subset,and Non-orthogonal multiple access(NOMA)technology,which enables massive user connectivity.However,However,using NOMA technology for successive interference cancellation calculation can result in a loss of user power.The introduction of power splitting factors makes it difficult to balance energy transmission and information security.The terahertz MIMO-NOMA system assisted by SWIPT has the disadvantage of high energy consumption,user resource planning and precoding algorithm design.Firstly,the energy efficiency optimization of the system is studied.An improved PAM user clustering algorithm is designed to cluster users according to the correlation of channel status information between users.The hybrid precoding of the sub-connected structure that require less radio frequency(RF)links are designed to serve each cluster.Finally,the Dinkelbach method is applied to transform the non-convex fractional programming problem into a subtractive form,MMSE expression and Sherman-Morrison-Woodbury formula are used to transform nonconvex problems into convex problems,and Dinkelbach alternating optimization algorithm is designed to obtain the optimal solution of energy efficiency.Secondly,the optimization of secure energy efficiency for systems is studied.In an effort to reduce the hardware overheads of a large phased array,transforming the traditional physical space channel model into a beamspace channel model in the angle domain.A matrix-vector-based user clustering algorithm was then designed to improve service quality for users.To minimize inter cluster interference among users by designing equivalent channel precoding on the basis of the strongest user.Dinkelbach’s method and the first order Taylor expansion are applied to transform the original non-convex secure energy efficiency optimization problem into a convex optimization problem in order to balance energy transmission and information security simultaneously,and an alternating optimization algorithm based on SCA and Dinkelbach is proposed in order to achieve the optimal solution for the secure energy efficiency.Lastly,(1)The simulation has verified that the designed improved PAM user clustering algorithm can more effectively partition users,the sub-connected structure mixed precoding algorithm can reduce hardware loss,and the Dinkelbach based alternating optimization algorithm achieves a compromise between energy utilization and information rate within the system,improving the energy efficiency of the system.(2)The simulation has verified that matrix-vector-based user clustering algorithm reduces mutual interference between users,and equivalent channel precoding on the basis of the strongest user can reduce hardware losses.The alternating optimization algorithm based on SCA and Dinkelbach can effectively reduce eavesdropping attacks on users and improve the security and energy efficiency of the system.