Dynamic Service Selection in Backscatter-Assisted RF-Powered Cognitive Networks: An Evolutionary Game Approach

Abstract

Conventional radio-frequency-powered cognitive networks can be combined with the backscatter communication technology to improve performance of the networks. In this paper, we consider a backscatter-assisted radio-frequency-powered cognitive network, where many secondary transmitters transmit data to a common secondary gateway. The secondary gateway, as a controller, provides two services for the secondary transmitters, and the secondary transmitters will adapt their service selection when their utilities are below the expected utility. To analyse the service selection of the secondary transmitters, we formulate the problem as an evolutionary game. Specifically, we model the service adaptation of the secondary transmitters by the replicator dynamics, and analytically prove that a unique evolutionary equilibrium is reached by the evolutionary game. Also, we prove that the evolutionary equilibrium is stable. We further present numerical results to provide insights of the dynamic service selection in the network.