UAV-Enabled Data Collection: Multiple Access, Trajectory Optimization, and Energy Trade-Off

Xiao, Lin; Liang, Yipeng; Weng, Chenfan; Yang, Dingcheng; Zhao, Qingmin

doi:10.1155/2019/9647539

Cited by 13 publications

(3 citation statements)

References 26 publications

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“…In this paper, we consider the case that there are no direct links between the UE and the BS owing to the long distances and blockages between them. Similar to [9,13,14,20,21], we assume the air-ground wireless channels are dominated by LoS links. e channel power gains from the UAV to the ground BS and from the UAV to the UE n, n ∈ N at time slot t, t ∈ T are, respectively, given as…”

Section: Channel Modelmentioning

confidence: 99%

Deep Reinforcement Learning-Based Dynamic Offloading Management in UAV-Assisted MEC System

Tian

Liu

Chai

et al. 2022

Wireless Communications and Mobile Computing

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Unmanned aerial vehicles (UAVs) have been envisioned as a promising technique to provide relaying and mobile edge computing (MEC) services for ground user equipment (UE). In this paper, we propose a UAV-assisted MEC architecture in dynamic environment, where a UAV flies with a fixed trajectory and may act as a MEC server to process the tasks offloaded from the UE or act as a relay to help the UE to offload their tasks to the ground base station (BS). The objective of this work is to maximize the long-term number of completed tasks of the UE. An optimization problem is formulated to optimize the task offloading decisions of the UE. Considering the random demands of the UE, a deep reinforcement learning- (DRL-) based algorithm is proposed to solve the formulated nonconvex optimization problem. Simulation results verify the effectiveness and correctness of the proposed algorithm.

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Section: Channel Modelmentioning

confidence: 99%

Deep Reinforcement Learning-Based Dynamic Offloading Management in UAV-Assisted MEC System

Tian

Liu

Chai

et al. 2022

Wireless Communications and Mobile Computing

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“…In the paper, the authors evaluated the impact of the UAV trajectory, the direction of the landing approach relative to radio beacons, and the temporal window of the signal analysis on the accuracy of the developed procedure. They indicated that the navigation error near the destination landing point is less than 1 m. In [17], an algorithm that combines optimal trajectory design and resource allocation scheme for multiple ground terminals with UAV arbitrary flight using the successive convex optimization and Lagrange duality is developed. The simulation results proved an increase in energy efficiency compared with the scheme without optimizing trajectory.…”

Section: Cargo Transport Levelmentioning

confidence: 99%

Unmanned Aerial Vehicles: A Literature Review

Shaaban¹,

Hassan²,

Gopalakrishnan³

et al. 2022

Journal of Hunan University Natural Sciences

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In recent years, Unmanned Aerial Vehicles (UAVs) have grown and increased in applications because of computational simplicity and adaptive control capacity with strong support from both civilian and military sectors. The applications of UAVs in various military, commercial and civilian areas have led to sustainable results. The application areas include but are not limited to oil & gas, cargo transport, geographic mapping, aerial photography, health care, and disaster management. The success of the UAV application missions is completely dependent on the accuracy in control provided by the flight controllers. Thus, there is a need for accurate, robust, and adaptive flight controllers. UAV dynamics modeling and identification and control of these vehicles are still major active areas of research and development. They pose severe challenges due to the vehicle's complex design, inherently nonlinear, and time-varying dynamics. The main goal of this paper is to identify the past research trends and recent improvements in UAVs. Furthermore, this paper discusses a comprehensive literature review according to the optimized objectives, solution techniques, and applications of UAVs such as Cargo Transport, Disaster Management, etc. According to the literature review, aerial photography is one of the applications of smart UAVs. The reliability of image matching across multiple camera perspectives, angles, and positions encourages computer vision approaches for UAV navigation, opening the way for future researchers to develop vision applications. This article presents a comprehensive literature review discussing the importance of UAV applications related to cost-effectiveness and versatility. Furthermore, a detailed survey of system modeling identification and control techniques is presented.

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“…The remarkable recent developments in drone technology have provided the opportunity to broadly deploy UAVs for wireless communication purposes, like aircraft, small aircraft, airships, and balloons. [21][22][23] The motivation behind this contribution is that in critical situations, drones can effectively deliver secure and low-cost solutions to the wireless network for a range of real-life situations when adequately deployed and operated. Given these exciting prospects for UAVs, several technical challenges need to be tackled and used effectively for each specific networking application.…”

Section: Motivations and Principal Contributionsmentioning

confidence: 99%

Unmanned aerial vehicles integratedHetNetfor smart dense urban area

Gupta

Rashid

et al. 2020

Trans Emerging Tel Tech

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Due to the massive growth of mobile users, the demand for data traffic along with coverage enhancement has significantly increased and put a significant burden on the pre-existing system like infrastructure based cellular networks, etc., especially in the urban zone. The inabilities and inefficiencies of pre-existing systems in handling a large number of traffic demands is a major concern. One way by which the existing infrastructure based cellular network can fulfill the above requirements by the increasing power level of radiations.But increasing the radiation power levels above a safety value defined by international exposure standards results in adverse health effects in the society. The impact is more on the urban societies because of congestion dwelling than rural areas. A vital solution to the above challenges of full filling the user's demand capacity as well as prevent the society from adverse health effects are to control ground-level data plane network aerially. That is not to make mobile users utterly dependent on the existing base stations. This could be possible through such as Loon Technology, Tethered Balloon, unmanned aerial vehicles (UAVs) concept, etc. The key objective is to efficiently deploy a HetNet wireless network using UAVs in urban canyons for great coverage and capacity enhancement and reduce the effects of radiations. The simulation results show the betterment in spectral efficiency, transmission range, transmission delays, and efficient packet delivery.

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UAV-Enabled Data Collection: Multiple Access, Trajectory Optimization, and Energy Trade-Off

Cited by 13 publications

References 26 publications

Deep Reinforcement Learning-Based Dynamic Offloading Management in UAV-Assisted MEC System

Deep Reinforcement Learning-Based Dynamic Offloading Management in UAV-Assisted MEC System

Unmanned Aerial Vehicles: A Literature Review

Unmanned aerial vehicles integratedHetNetfor smart dense urban area

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