  In this paper, we investigate optimal scheme to manage time scheduling of
different modules including spectrum sensing, radio frequency (RF) energy
harvesting (RFH) and ambient backscatter communication (ABCom) by maximizing
data transmission rate in the internet of things (IoT). We first consider using
spectrum sensing with energy detection techniques to detect high power ambient
RF signals, and then performing RFH and ABCom with them. Specifically, to
improve the spectrum sensing efficiency, compressive sensing is used to detect
the wideband RF singals. We propose a joint optimization problem of optimizing
time scheduling parameter and power allocation ratio, where power allocation
ratio appears because REH and ABCom work at the same time. In addition, a
method to find the threshold of spectrum sensing for backscatter communication
by analyzing the outage probability of backscatter communication is proposed.
Numerical results demonstrate that the optimal schemes with spectrum sensing
are achieved with larger transmission rates. Compressive sensing based method
is confirmed to be more efficient, and that the superiorities become more
obvious with the increasing of the network operation time. Moreover, the
optimal scheduling parameters and power allocation ratios are obtained. Also,
simulations illustrate that the threshold of spectrum sensing for backscatter
communication is obtained by analyzing the outage probability of backscatter
communication.
