Cooperative Trajectory Design and Resource Allocation for a Two-UAV Two-User Wireless Powered Communication System

Xie, Lifeng; Xu, Jie

doi:10.1109/iccs.2018.8689238

Cited by 11 publications

(22 citation statements)

References 18 publications

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“…where the equality holds for (24) when z = z 0 and z ′ = z ′ 0 . Thus, the inequality in (21) is tight for…”

Section: Trajectory Optimizationmentioning

confidence: 99%

“…Although the optimization problem (P2.1) is still non-convex, we can obtain the solution through SCP and BCD techniques [23,24]. In the following, time allocation B = {δ I [n], δ E [n]}, GNs' transmit power C = {Q i [n]} and UAVs' trajectories A = {q i [n]} can be obtained by considering the others as given in an alternating manner.…”

Section: Solution Of Casementioning

confidence: 99%

“…Ref. [11,24] studied two-UAVs and two-GNs wireless powered network to maximize the minimum throughput of GNs with the flight speed and users energy constraints. In [25], a multi-UAV and multi-ground-nodes IoT wireless powered network is studied, in which UAVs serve GNs through time division multiple address.…”

Section: Introductionmentioning

confidence: 99%

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Resource and trajectory optimization in UAV-powered wireless communication system

et al. 2021

Sci. China Inf. Sci.

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The unmanned aerial vehicle (UAV) is a promising enabler of Internet of Things (IoT) owing to its highly flexible features. Combined with wireless power transfer (WPT) techniques, a UAV can provide energy for IoT nodes, which can extend the lifetime of energy constrained communication systems. This paper studies resource and trajectory optimization in UAV-powered wireless communication systems, which consists of two UAVs and two ground nodes (GNs). The system works in a way that the two UAVs alternately charge the two GNs through wireless power transfer and two GNs also alternately send their information to the corresponding UAV with the harvested energy, which can effectively reduce the interference while receiving the information of GNs. Aiming to maximize the minimum throughput of two GNs, wireless resource and UAVs' trajectories are jointly optimized with the constraints of UAV collision avoidance, flying speed, and transmit power. Successive convex programming (SCP) and block coordinate descent (BCD) are utilized to solve the optimization problem. Simulation results show that the proposed scheme achieves larger minimum throughput than the benchmark scheme.

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“…where the equality holds for (24) when z = z 0 and z ′ = z ′ 0 . Thus, the inequality in (21) is tight for…”

Section: Trajectory Optimizationmentioning

confidence: 99%

Section: Solution Of Casementioning

confidence: 99%

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Resource and trajectory optimization in UAV-powered wireless communication system

et al. 2021

Sci. China Inf. Sci.

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“…and θ k,m [n] denotes the random phase of the wireless channel that is assumed as a uniformly distributed random variable in [0, 2π), and independent over time and different UAV-device pairs. 1 We also assume that the downlink WPT and uplink WIT use the same frequency band but over orthogonal time instants. Therefore, due to channel reciprocity, at any time slot n ∈ N , the wireless channels for both uplink WIT and downlink WPT are identical.…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…With interference coordination, each of the two UAVs sends independent energy signals to the ground IoT-devices and individually decodes the information signals received from its associated First, we consider the downlink WPT at time slot n ∈ N with duration δ E [n], during which each UAV m ∈ {1, 2} transmits independent energy signals s m [n] for charging the two IoT- 1 The assumption of the uniformly distributed random phases is explained as follows. At any slot n, we have θ k,m (t) = 2π λd k,m (t), ∀t ∈ Tn, where λ denotes the signel wavelength that generally takes a very small value (e.g., 1/3 m at the frequency of 900 MHz).…”

Section: A Scenario With Interference Coordinationmentioning

confidence: 99%

Common Throughput Maximization for UAV-Enabled Interference Channel With Wireless Powered Communications

Xie

Zeng

2020

IEEE Trans. Commun.

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This paper studies an unmanned aerial vehicle (UAV)-enabled two-user interference channel for wireless powered communication networks (WPCNs), in which two UAVs wirelessly charge two lowpower Internet-of-things (IoT)-devices on the ground and collect information from them. We consider two scenarios when both UAVs cooperate in energy transmission and/or information reception via interference coordination and coordinated multi-point (CoMP), respectively. For both scenarios, the UAVs' controllable mobility is exploited via trajectory design to not only enhance the wireless power transfer (WPT) efficiency in the downlink, but also mitigate the co-channel interference for wireless information transfer (WIT) in the uplink. In particular, the objective is to maximize the uplink common (minimum) throughput of the two IoT-devices over a finite UAV mission period, by jointly optimizing the trajectories of both UAVs and the downlink/uplink wireless resource allocation, subject to the maximum flying speed and collision avoidance constraints at UAVs, as well as the individual energy neutrality constraints at IoT-devices. Under both scenarios of interference coordination and CoMP, we first obtain the optimal solutions to the two common-rate maximization problems in well structures for the special case with sufficiently long UAV mission duration. Next, we obtain high-quality solutions for the practical case with finite UAV mission duration by using the alternating optimization and successive convex approximation (SCA).Unmanned aerial vehicle (UAV), wireless powered communication networks (WPCN), wireless power transfer (WPT), coordinated multi-point (CoMP), trajectory optimization, resource allocation.

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Placement Optimization for UAV-Enabled Wireless Power Transfer System

Wang

Yang

Zhang

et al. 2021

Communications and Networking

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Cooperative Trajectory Design and Resource Allocation for a Two-UAV Two-User Wireless Powered Communication System

Cited by 11 publications

References 18 publications

Resource and trajectory optimization in UAV-powered wireless communication system

Resource and trajectory optimization in UAV-powered wireless communication system

Common Throughput Maximization for UAV-Enabled Interference Channel With Wireless Powered Communications

Placement Optimization for UAV-Enabled Wireless Power Transfer System

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