Abstract: In simultaneous wireless information and power transfer networks,multiple antennas are usually equipped at the transmitter,which is able to serve all sensors in one-time transmission over the same frequency band.However,collecting channel state information from all sensors may cause a colossal waste of time and frequency resources.Therefore,the energy-saving beamfor-ming design with only channel distribution information at the transmitter is studied in multi-user multi-input single-output network.Under the constraints of information interruption probability,total available power and available power of authorized users,the network energy efficiency is maximized by the improved teaching-learning-based optimization algorithm.In addition,for the proposed power consumption scheme,the nonlinear energy receiving mechanism is considered,and the power-splitting energy harvesting receiver architecture is proposed to prevent the receiver from entering the saturation region,so as to improve the power receiving efficiency.The improved teaching-learning-based optimization algorithm has the advantages of whale algorithm,solves the constructed nonconvex optimization problem,and improves the convergence speed.Simulation experiments analyze the effects of outage probability,dynamic power consumption coefficient and available power at the transmitter on the system energy efficiency in the dynamic energy allocation scenario,and verify the effectiveness of the proposed algorithm.

Key words: Simultaneous wireless information and power transfer, Energy efficiency, Non-linear energy receiving model, Swarm intelligence optimization algorithm