  In this paper, we introduce a new model for RF-powered cognitive radio
networks with the aim to improve the performance for secondary systems. In our
proposed model, when the primary channel is busy, the secondary transmitter is
able either to backscatter the primary signals to transmit data to the
secondary receiver or to harvest RF energy from the channel. The harvested
energy then will be used to transmit data to the receiver when the channel
becomes idle. We first analyze the tradeoff between backscatter communication
and harvest-then-transmit protocol in the network. To maximize the overall
transmission rate of the secondary network, we formulate an optimization
problem to find time ratio between taking backscatter and harvest-then-transmit
modes. Through numerical results, we show that under the proposed model can
achieve the overall transmission rate higher than using either the backscatter
communication or the harvest-then-transmit protocol.
