  Wireless powered backscatter communications (WPBC) is capable of implementing
ultra-low-power communication, thus promising in the Internet of Things (IoT)
networks. In practice, however, it is challenging to apply WPBC in large-scale
IoT networks because of its short communication range. To address this
challenge, this paper exploits an unmanned ground vehicle (UGV) to assist WPBC
in large-scale IoT networks. In particular, we investigate the joint design of
network planning and dynamic resource allocation of the access point (AP), tag
reader, and UGV to minimize the total energy consumption. Also, the AP can
operate in either half-duplex (HD) or full-duplex (FD) multiplexing mode. Under
HD mode, the optimal cell radius is derived and the optimal power allocation
and transmit/receive beamforming are obtained in closed form. Under FD mode,
the optimal resource allocation, as well as two suboptimal ones with low
computational complexity, is developed. Simulation results disclose that
dynamic power allocation at the tag reader rather than at the AP dominates the
network energy efficiency while the AP operating in FD mode outperforms that in
HD mode concerning energy efficienc
