Age of Information Based Scheduling for UAV Aided Emergency Communication Networks

Liang, Tianhao; Li, Wentao; Yang, Jiayan; Zhang, Tingting

doi:10.1109/icc45855.2022.9838496

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…Different from most UAV wireless communication models that utilize the free space path loss model to establish a deterministic relation between the geographic coordinates and channels, 28 this work employs the path loss average model considering the both LoS and NLoS links, that is, weighted sum model of both LoS and NLoS links, which is convenient for the optimal trajectory design and resource allocation of the considered system 31 …”

Section: System Model and Assumptionsmentioning

confidence: 99%

Physical layer security‐oriented energy‐efficient resource allocation and trajectory design for UAV jammer over 5G millimeter wave cognitive relay system

Sun,

Jia,

Han

et al. 2023

Trans Emerging Tel Tech

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This work focuses on the optimal trajectory of a rotary‐wing unmanned aerial vehicle (UAV) jammer and the system power allocation with the objective of maximizing the total secure energy efficiency (EE) of a slotted relay‐assisted millimeter wave (mm‐Wave) cognitive radio system. The UAV flies from starting location to final one in a round of communication mission that is overheard by a malicious eavesdropper. The network terminals are equipped with multiple‐input multiple‐output (MIMO) antenna array. This work first develops a practical approximation propagation model by addressing three key challenges: path loss, small‐scale Nakagami‐m fading channel gains, and transceiver antenna beamforming gains. By using the approximate model, the upper and lower bounds of the ergodic rate of each communication link are derived. Second, with the objective of maximizing secure EE, the optimal UAV trajectory and system resource allocation framework is established by considering the constraints of interference at primary receiver (PR), information‐causality relationship, rotary‐wing UAV propulsion energy and so forth. The optimal framework is solved with a tractable CVX tool by using the derived upper and lower bounds and successive convex approximation. Finally, an iterative optimizing algorithm is established by using Dinkelbach's method. In the simulation, the work presents the comparison of UAV trajectories, secure rates, and secure EEs of three schemes, that is, the proposed EE scheme, the non‐EE scheme where only the optimal secure rate is considered, and the EE scheme with the consideration of all communication‐related energy consumption. The simulations show that the EE schemes achieve smoother UAV trajectory than non‐EE, but the non‐EE scheme has higher secure rate. The impact of communication energy consumption is negligible. In addition, the effect of MIMO antenna array and mm‐Wave on system performance is exploited.

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Section: System Model and Assumptionsmentioning

confidence: 99%

Physical layer security‐oriented energy‐efficient resource allocation and trajectory design for UAV jammer over 5G millimeter wave cognitive relay system

Sun,

Jia,

Han

et al. 2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…AoI minimization in WSNs and Internet of things (IoTs) is studied in [ 27 , 28 ]. UAV trajectory design to ensure the timeliness of information in an emergency network is evaluated in [ 29 ]. However, not much literature is available on AoI minimization concerning emergency networks.…”

Section: Introductionmentioning

confidence: 99%

On Coverage of Critical Nodes in UAV-Assisted Emergency Networks

Waheed

Ahmad

Ahmed

et al. 2023

Sensors

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Unmanned aerial vehicle (UAV)-assisted networks ensure agile and flexible solutions based on the inherent attributes of mobility and altitude adaptation. These features render them suitable for emergency search and rescue operations. Emergency networks (ENs) differ from conventional networks. They often encounter nodes with vital information, i.e., critical nodes (CNs). The efficacy of search and rescue operations highly depends on the eminent coverage of critical nodes to retrieve crucial data. In a UAV-assisted EN, the information delivery from these critical nodes can be ensured through quality-of-service (QoS) guarantees, such as capacity and age of information (AoI). In this work, optimized UAV placement for critical nodes in emergency networks is studied. Two different optimization problems, namely capacity maximization and age of information minimization, are formulated based on the nature of node criticality. Capacity maximization provides general QoS enhancement for critical nodes, whereas AoI is focused on nodes carrying critical information. Simulations carried out in this paper aim to find the optimal placement for each problem based on a two-step approach. At first, the disaster region is partitioned based on CNs’ aggregation. Reinforcement learning (RL) is then applied to observe optimal placement. Finally, network coverage over optimal UAV(s) placement is studied for two scenarios, i.e., network-centric and user-centric. In addition to providing coverage to critical nodes, the proposed scheme also ensures maximum coverage for all on-scene available devices (OSAs).

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An AoI-Guaranteed Sensor Data Collection Strategy for RIS-assisted UAV Communication System

Yang,

Yu,

et al. 2023

2023 IEEE/CIC International Conference on Communications in China (ICCC)

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Age of Information Based Scheduling for UAV Aided Emergency Communication Networks

Cited by 6 publications

References 14 publications

Physical layer security‐oriented energy‐efficient resource allocation and trajectory design for UAV jammer over 5G millimeter wave cognitive relay system

Physical layer security‐oriented energy‐efficient resource allocation and trajectory design for UAV jammer over 5G millimeter wave cognitive relay system

On Coverage of Critical Nodes in UAV-Assisted Emergency Networks

An AoI-Guaranteed Sensor Data Collection Strategy for RIS-assisted UAV Communication System

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