Cooperative Communication via Automated Guided Vehicle and Unmanned Aerial Vehicle: A Distributed Collaborate Beamforming Method

Abstract

The advantages of autonomy, stability, and high load capability make automated guided vehicles (AGVs) appealing for applications like intelligent transportation networks. Nevertheless, AGVs may face limitations in terms of flexibility and transmission efficiency. In this paper, we consider the scenario where unmanned aerial vehicles (UAVs) serve dual roles in enhancing the communications of AGVs. Specifically, one group of UAVs is employed to support AGVs in data transmission, while another group of UAVs equipped with computational resources, functions as aerial base stations (ABSs) for receiving and processing the collected data. Following this, we explore the collaborative deployment between AGVs and UAVs, and propose a highly efficient, low-interference, and energy-efficient uplink data transmission framework based on distributed collaborative beamforming. Correspondingly, we formulate a high-performance and low-interference transmission multi-objective optimization problem (HLTMOP) to reduce the transmission time and operation energy consumption of the AGVs and UAVs, while minimizing the total sidelobe levels toward the directions of all non-current receiving ABSs. Due to the NP-hardness of the HLTMOP, we propose a swarm intelligence algorithm, namely, improved multi-objective ant lion optimization (IMOALO), with three improved operators. Simulation results show that the proposed IMOALO algorithm performs better and can generate more excellent solutions than other benchmark algorithms.