Fair-Energy Trajectory Planning for Cooperative UAVs to Locate Multiple Targets

Ji, Yao; Dong, Chao; Zhu, Xiaojun; Wu, Qihui

doi:10.1109/icc.2019.8761892

Cited by 10 publications

(2 citation statements)

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“…Generally, RSS measurements are easy to obtain in many wireless networks and does not require stringent synchronization and calibration constraints associated with timing based measurements. The works in [8]- [10] assumed that the UAV flies high enough so that the RSS of the UAVuser or Air-to-ground (A2G) link is modeled as a simple line-of-sight (LoS) channel. This LoS assumption is generally not valid in urban scenarios as A2G links are often blocked by city buildings.…”

Section: Introductionmentioning

confidence: 99%

UAV-aided Wireless Node Localization Using Hybrid Radio Channel Models

Esrafilian¹,

Gangula²,

Gesbert³

2022

Preprint

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This paper considers the problem of ground user localization based on received signal strength (RSS) measurements obtained by an unmanned aerial vehicle (UAV). We treat UAV-user link channel model parameters and antenna radiation pattern of the UAV as unknowns that need to be estimated. A hybrid channel model is proposed that consists of a traditional path loss model combined with a neural network approximating the UAV antenna gain function. With this model and a set of offline RSS measurements, the unknown parameters are estimated. We then employ the particle swarm optimization (PSO) technique which utilizes the learned hybrid channel model along with a 3D map of the environment to accurately localize the ground users. The performance of the developed algorithm is evaluated through simulations and also real-world experiments.

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Section: Introductionmentioning

confidence: 99%

UAV-aided Wireless Node Localization Using Hybrid Radio Channel Models

Esrafilian¹,

Gangula²,

Gesbert³

2022

Preprint

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“…Although the advantages of a single UAV have been demonstrated in enhancing the performance of wireless networks [8]- [10], it has limited capability in general and may not satisfy the communication requirement due to the size, weight, and power (SWAP) constraints [11]. Besides, in single-site positioning, multiple distance measurements from a single UAV on same targets may lead to large accumulated errors [6]. A multi-UAV system can potentially overcome these problems.…”

mentioning

confidence: 99%

Constrained Utility Maximization in Dual-Functional Radar-Communication Multi-UAV Networks

Wang

Fei

Zhang

et al. 2021

IEEE Trans. Commun.

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In this paper, we investigate the network utility maximization problem in a dual-functional radar-communication multi-unmanned aerial vehicle (multi-UAV) network where multiple UAVs serve a group of communication users and cooperatively sense the target simultaneously. To balance the communication and sensing performance, we formulate a joint UAV location, user association, and UAV transmission power control problem to maximize the total network utility under the constraint of localization accuracy. We then propose a computationally practical method to solve this NP-hard problem by decomposing it into three sub-problems, i.e., UAV location optimization, user association and transmission power control. Three mechanisms are then introduced to solve the three sub-problems based on spectral clustering, coalition game, and successive convex approximation, respectively. The spectral clustering result provides an initial solution for user association. Based on the three mechanisms, an overall algorithm is proposed to iteratively solve the whole problem. We demonstrate that the proposed algorithm improves the minimum user data rate significantly, as well as the fairness of the network. Moreover, the proposed algorithm increases the network utility with a lower power consumption and similar localization accuracy, compared to conventional techniques.

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