  In this paper, we study the transmission strategy adaptation problem in an
RF-powered cognitive radio network, in which hybrid secondary users are able to
switch between the harvest-then-transmit mode and the ambient backscatter mode
for their communication with the secondary gateway. In the network, a monetary
incentive is introduced for managing the interference caused by the secondary
transmission with imperfect channel sensing. The sensing-pricing-transmitting
process of the secondary gateway and the transmitters is modeled as a
single-leader-multi-follower Stackelberg game. Furthermore, the follower
sub-game among the secondary transmitters is modeled as a generalized Nash
equilibrium problem with shared constraints. Based on our theoretical
discoveries regarding the properties of equilibria in the follower sub-game and
the Stackelberg game, we propose a distributed, iterative strategy searching
scheme that guarantees the convergence to the Stackelberg equilibrium. The
numerical simulations show that the proposed hybrid transmission scheme always
outperforms the schemes with fixed transmission modes. Furthermore, the
simulations reveal that the adopted hybrid scheme is able to achieve a higher
throughput than the sum of the throughput obtained from the schemes with fixed
transmission modes.
