UGV-assisted Wireless Powered Backscatter Communications for Large-Scale IoT Networks

TL;DR

This paper proposes using unmanned ground vehicles to enhance wireless powered backscatter communications in large-scale IoT networks, optimizing energy efficiency through joint network planning and resource allocation.

Contribution

It introduces a novel UGV-assisted framework for WPBC in large-scale IoT, including optimal strategies for cell radius, power, and beamforming in HD and FD modes.

Findings

FD mode outperforms HD mode in energy efficiency

Dynamic power allocation at the tag reader is crucial for energy savings

Optimal cell radius and resource allocation strategies are derived

Abstract

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