Age-Based Path Planning and Data Acquisition in UAV-Assisted IoT Networks

Jia, Zekun; Qin, Xiaoqi; Wang, Zijing; Liu, Baoling

doi:10.1109/iccw.2019.8756751

Cited by 67 publications

(42 citation statements)

References 11 publications

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“…In [21], the UAV's trajectory was optimized to minimize both the average AoI of the system and the maximum AoI of different wireless sensors, where the UAV was used to collect the SNs' data. In [22], the UAV's trajectory and data acquisition mode were jointly optimized to minimize average AoI of all the SNs, where the UAV was allowed to acquire the data in hovering, flying or hybrid mode. In [23], a UAV's trajectory planning strategy was proposed to minimize the maximum AoI of a UAV-enabled wireless sensor network, where the balance between the SNs' uploading time and the UAV's flight time was achieved.…”

Section: B Related Workmentioning

confidence: 99%

AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks

Xiong

et al. 2021

IEEE Internet Things J.

243

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Section: B Related Workmentioning

confidence: 99%

AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks

Xiong

et al. 2021

IEEE Internet Things J.

243

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“…In [19], a UAV trajectory planning model for data collection was proposed taking into account the message expiration. Also, in [20], age of information was considered as a performance metric to measure the data freshness in UAV-aided IoT networks. In [21], a UAVaided data collection design was proposed, where the UAV's trajectory, velocity, altitude and data link were all considered to minimize the mission time.…”

Section: B Related Workmentioning

confidence: 99%

Time Allocation and Optimization in UAV-Enabled Wireless Powered Communication Networks

Yan

Chen

Yang

2022

IEEE Trans. on Green Commun. Netw.

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“…This paper optimizes the minimization of the average AoI (AAoI) of various wireless sensors, where the UAV is used to collect the ground sensor nodes (SNs) data. The authors in [20] proposed joint optimization of the UAV trajectory and data collection based on dynamic programming. The paper try to minimize AoI of the SNs, independent form the UAV flight mode.…”

Section: B Related Workmentioning

confidence: 99%

AI-based Radio Resource Management and Trajectory Design for PD-NOMA Communication in IRS-UAV Assisted Networks

Hariz¹,

Sheikhzadeh²,

Mokari³

et al. 2021

Preprint

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In this paper, we consider that the unmanned aerial vehicles (UAVs) with attached intelligent reflecting surfaces (IRSs) play the role of flying reflectors that reflect the signal of users to the destination, and utilize the power-domain non-orthogonal multiple access (PD-NOMA) scheme in the uplink. We investigate the benefits of the UAV-IRS on the internet of things (IoT) networks that improve the freshness of collected data of the IoT devices via optimizing power, sub-carrier, and trajectory variables, as well as, the phase shift matrix elements. We consider minimizing the average age-of-information (AAoI) of users subject to the maximum transmit power limitations, PD-NOMA-related restriction, and the constraints related to UAV's movement. The optimization problem consists of discrete and continuous variables. Hence, we divide the resource allocation problem into two sub-problems and use two different reinforcement learning (RL) based algorithms to solve them, namely the double deep Qnetwork (DDQN) and a proximal policy optimization (PPO). Our numerical results illustrate the performance gains that can be achieved for IRS enabled UAV communication systems. Moreover, we compare our deep RL (DRL) based algorithm with matching algorithm and random trajectory, showing the combination of DDQN and PPO algorithm proposed in this paper performs 10% and 15% better than matching algorithm and random-trajectory algorithm, respectively.

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Age-Based Path Planning and Data Acquisition in UAV-Assisted IoT Networks

Cited by 67 publications

References 11 publications

AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks

AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks

Time Allocation and Optimization in UAV-Enabled Wireless Powered Communication Networks

AI-based Radio Resource Management and Trajectory Design for PD-NOMA Communication in IRS-UAV Assisted Networks

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