Multiobjective UAV Path Planning for Emergency Information Collection and Transmission

Huang, Zhengrui; Chen, Chongcheng; Pan, Miaoxin

doi:10.1109/jiot.2020.2979521

Cited by 85 publications

(36 citation statements)

References 48 publications

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“…Although excellent research has been conducted on UAV communications, there are few works focusing on UAV-assisted emergency communication networks in disasters [26][27][28][29]. Merwaday et al [26] used a genetic algorithm to get the best location of the UAV, thereby improving the network throughput.The problem that maximizing the number of service users under limited UAV battery capacity by optimizing the flight path was proposed in [27].…”

Section: A Motivations and Related Workmentioning

confidence: 99%

“…There are three different network models corresponding to three scenarios: First, UAV is deployed to assist the surviving BSs; Second, when all ground BSs are destroyed, UAV serves as a flying base station to provide communication services; In addition, hovering UAVs are used as multi-hop relays to exchange the information between the disaster area and outside. The collection and transmission of user information in emergency scenarios considering natural environment and UAV energy consumption constraints were investigated in [29]. In order to improve the QoE and shorten the flight time of UAV, a path optimization scheme including hover point selection and mobility planning is proposed and solved by convex optimization method.…”

Section: A Motivations and Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Trajectory Optimization for UAV Emergency Communication With Limited User Equipment Energy: A Safe-DQN Approach

Zhang

Lei

Liu

et al. 2021

IEEE Trans. on Green Commun. Netw.

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In post-disaster scenarios, it is challenging to provide reliable and flexible emergency communications, especially when the mobile infrastructure is seriously damaged. This article investigates the unmanned aerial vehicle (UAV)-based emergency communication networks, in which UAV is used as the mobile aerial base station for collecting information from ground users in affected areas. Due to the breakdown of ground power system after disasters, the available energy of affected user equipment (UE) is limited. Meanwhile, with the complex geographical conditions after disasters, there are obstacles affecting the flight of UAV. Aiming at maximizing the uplink throughput of UAV networks during the flying time, we formulate the UAV trajectory optimization problem considering UE energy limitation and location of obstacles on the ground. Since the constraint on UE energy is dynamic and longterm cumulative, it is hard to be solved directly. We transform the problem into a constrained Markov decision-making process (CMDP) with UAV as agent. To tackle the CMDP, we propose a safe-deep-Qnetwork (safe-DQN) based UAV trajectory design algorithm, where the UAV learns to selects the optimal action in reasonable policy sets. Simulation results reveal that: i) the uplink throughput of the proposed algorithm converges within multiple iterations; and ii) compared with the benchmark algorithms, the proposed algorithm performs better in terms of uplink throughput and UE energy efficiency, achieving a good trade-off between UE energy consumption and uplink throughput.

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Section: A Motivations and Related Workmentioning

confidence: 99%

Section: A Motivations and Related Workmentioning

confidence: 99%

Trajectory Optimization for UAV Emergency Communication With Limited User Equipment Energy: A Safe-DQN Approach

Zhang

Lei

Liu

et al. 2021

IEEE Trans. on Green Commun. Netw.

View full text Add to dashboard Cite

show abstract

“…Data collection from desired regions, while avoiding forbidden regions and reaching the destination [43] min Time Joint optimization of the data collection intervals, the UAV's speed, and the sensors' transmit powers [44] max QoI UAV's trajectory, the time required for energy harvesting and data collection for each SN, are jointly optimized [45] [55] min Time Joint optimization of the UAV trajectory, as well as the wake-up scheduling and association for SNs, while ensuring successful data upload with a given energy budget [56] min Cost Joint optimization of the UAV trajectory with wake-up time allocation and the transmit power…”

Section: Ref Objective Remarksmentioning

confidence: 99%

Joint Optimization of Sensors Association and UAVs Placement in IoT Applications With Practical Network Constraints

2021

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“…A robust routing scheme is introduced to guarantee communication stability during the process of delivering the distress information. A novel UAV path planning frame work is introduced in [ 12 ] for emergency messages transmission and collection. The motion and transmission power of the UAV is optimized while visiting access points for sending and collecting the emergency messages.…”

Section: Introductionmentioning

confidence: 99%

UAV-Based Intelligent Transportation System for Emergency Reporting in Coverage Holes of Wireless Networks

Almasoud

2021

Sensors

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During critical moments, disaster and accident victims may not be able to request help from the emergency response center. This may happen when the victim’s vehicle is located within a coverage hole in a wireless network. In this paper, we adopt an unmanned aerial vehicle (UAV) to work as an automatic emergency dispatcher for a user in a vehicle facing a critical condition. Given that the UAV is located within a coverage hole and a predetermined critical condition is detected, the UAV becomes airborne and dispatches distress messages to a communication network. We propose to use a path loss map for UAV trajectory design, and we formulate our problem mathematically as an Integer Linear Program (ILP). Our goals are to minimize the distress messages delivery time and the UAV’s mission completion time. Due to the difficulty of obtaining the optimal solution when the scale of the problem is large, we proposed an efficient algorithm that reduces the computational time significantly. We simulate our problem under different scenarios and settings, and study the performance of our proposed algorithm.

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Multiobjective UAV Path Planning for Emergency Information Collection and Transmission

Cited by 85 publications

References 48 publications

Trajectory Optimization for UAV Emergency Communication With Limited User Equipment Energy: A Safe-DQN Approach

Trajectory Optimization for UAV Emergency Communication With Limited User Equipment Energy: A Safe-DQN Approach

Joint Optimization of Sensors Association and UAVs Placement in IoT Applications With Practical Network Constraints

UAV-Based Intelligent Transportation System for Emergency Reporting in Coverage Holes of Wireless Networks

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