Research On Duplex Relay Technology And Security Energy Efficiency In Wireless Cognitive Energy Harvesting Networks

In the 5G era of all things smart,with the explosion of wireless communication data,the lack of spectrum resources and the intensification of energy consumption are the dual pressures faced by wireless communication systems.Cognitive radio(CR)technology allows primary and secondary users to exchange data on the same authorized spectrum,which improves the spectrum utilization.Radio frequency(RF)based simultaneous wireless information and power transfer(SWIPT)technology realizes the simultaneous interaction information and transmission energy,and prolongs the life of energy limited networks.Therefore,it is very important to study SWIPT in CR networks with limited energy to improve both spectrum efficiency and energy efficiency.This thesis mainly studies the wireless cognitive energy harvesting communication network,on the premise of ensuring the service quality of users,an optimal allocation algorithm is proposed to maximize the energy efficiency(EE)of the system.Firstly,aiming at the problem of self-interference(SI)suppression,this thesis studies how to collect self-interference energy in full-duplex(FD)amplification and forwarding(AF)relay network by SWIPT technology,and maximizes the total harvested energy by jointly optimizing the transmit power and the power allocation factor at the source nodes,as well as the beamforming matrix and the an covariance matrix at the relay.In addition,considering that confidential information will be stolen by illegal users,artificial noise is simultaneously emitted at the relay to confuse eavesdroppers,which improves the physical layer security.On this basis,an alternative optimization iterative algorithm is proposed to obtain the optimal solution.Numerical results show that compared with other benchmark schemes,the full-duplex optimization scheme proposed in this thesis significantly improves the energy acquisition.Secondly,focusing on the radio frequency based wireless energy transmission in the MISO CR network is studied to maximize the energy efficiency,the energy efficiency optimization problems in perfect channel state information(CSI)and statistical CSI scenarios are deeply studied.For perfect CSI,the non-convex original problem to be optimized is transformed into a subtraction form which is easy to solve,and then a two-stage iterative algorithm based on Dinkelbach is proposed to solve the optimization problem by using successive convex approximation(SCA).However,in the statistical CSI scene,due to the constraint of outage probability,it is necessary to use Bernstein inequality to transform the original problem into an equivalent problem with closed expression.By introducing auxiliary variables,a new two-stage optimization algorithm is designed to calculate the corresponding optimal beamforming vector.Numerical results show that the algorithms proposed in this thesis,after a finite number of iterations can converge to the optimal energy efficiency.