Trajectory Optimization and Power Allocation for Multi-Hop UAV Relaying Communications
Author(s) -
Guangchi Zhang,
Haiqiang Yan,
Yong Zeng,
Miao Cui,
Yijun Liu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2868117
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Unmanned aerial vehicles (UAVs) have found important applications in wireless communications due to their ability for on-demand and swift deployment, high mobility, and high probability of line-of-sight communication link with the ground. For UAV-enabled wireless communications, one of the main use cases is UAV relaying, where UAVs are deployed as flying relays in the sky to provide wireless connections between distant users that do not have reliable direct connectivity. This paper considers a general multiple UAV relaying system, where the information from a source node to a destination node is forwarded through multi-hop UAV relays. We aim to maximize the end-to-end throughput via joint UAV trajectory and transmit power optimization, subject to UAV mobility and collision avoidance constraints, the information-causality constraints, and the average and peak transmit power constraints of the source and UAV relays. The formulated problem is non-convex and challenging to solve, hence we propose an efficient iterative algorithm to obtain a suboptimal solution based on the alternating maximization and successive convex optimization techniques. Numerical results validate the effectiveness of the proposed algorithm as compared to three benchmark schemes with only transmit power allocation or trajectory optimization.
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