Multi-UAV Collaborative Sensing and Communication: Joint Task Allocation and Power Optimization
Kaitao Meng, Xiaofan He, Qingqing Wu, and Deshi Li

TL;DR
This paper introduces a novel multi-UAV cooperative sensing and transmission scheme with replicated task allocation, optimizing task distribution and power to minimize mission completion time through advanced optimization techniques.
Contribution
It proposes a new replicated sensing task allocation scheme and formulates an optimization problem, solved via monotonic optimization and auxiliary variables, to improve multi-UAV sensing efficiency.
Findings
Replicated sensing reduces overall mission completion time.
The optimization problem is effectively solved using the Polyblock algorithm.
Closed-form solutions are derived for non-replicated sensing cases.
Abstract
Compared to a single UAV with limited sensing coverage and communication capability, multi-UAV cooperation is able to provide more effective sensing and transmission (S&T) services. Nevertheless, most existing works on multi-UAV sensing mainly focus on mutually exclusive task allocation and independent data transmission, which did not fully exploit the benefit of multi-UAV sensing and communication. Motivated by this, we propose a novel multi-UAV cooperative S&T scheme with replicated sensing task allocation. Although replicated task allocation may sound counter-intuitive, it can actually foster cooperative transmission among multiple UAVs and thus reduce the overall sensing mission completion time. To obtain the optimal task allocation and transmit power of the proposed scheme, a mission completion time minimization problem is formulated. To solve this problem, a necessary condition…
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Taxonomy
TopicsUAV Applications and Optimization · Distributed Control Multi-Agent Systems · Advanced Wireless Communication Technologies
