A resource optimization scheme for wireless powered semantic communication networks
In order to address the energy supply limitation of users in semantic communication systems,a wireless powered semantic communication network(WPSCN)based on a nonlinear energy harvesting model is proposed.In the proposed WPSCN,a hybrid access point(HAP)transmits radio frequency signals to all users simultaneously to realize remote energy supply,and then the users use the harvested energy to transmit semantic information to the HAP via time-division-multiple-access.Under this setup,the problem of maximizing the sum of the effective semantic information of all users is investigated.It is a joint optimization problem covering the transmit power at the users,the transmit beamforming vector at the HAP,and time allocation.As the formulated problem contains an implicit objective function,it is difficult to solve directly.To address this challenge,an explicit function of semantic similarity is obtained by using the generalized function approximation.Then,an alternating optimization algorithm based on the successive convex approximation(SCA)and semi-definite relaxation(SDR)is designed to deal with the non-convexity.Simulation results verify that the proposed scheme can significantly improve the sum of effective semantic information compared to the benchmark schemes.
semantic communicationwireless powered semantic communication network(WPSCN)semantic similarityjoint optimization
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