Joint Power and Channel Allocation for Safeguarding Cognitive Satellite-UAV Networks

Lei, Chengleyang; Feng, Wei; Chen, Yunfei; Ge, Ning

doi:10.1109/globecom46510.2021.9685509

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…In order to improve the spectrum efficiency, the cognitive satellite-UAV network, in which UAV users and satellite users can share the same time-frequency resource, is considered by a lot of works [9], [10]. Since the distance from the satellite to ground is farther, the power control of the UAVs should be optimized carefully to reduce the interference to the satellite users.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Optimization and Power Allocation for Cell-Free Satellite-UAV Internet of Things

Wang

2023

IEEE Access

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Massive access outside the coverage of terrestrial cellular networks will be the main feature of the sixth generation (6G) networks. In order to cope with it, the cognitive satellite-UAV network (CSUN) has drawn a lot of attentions. In this paper, we investigate the UAV trajectory optimization and power allocation for the cell-free CSUN consisting of one satellite and a swarm of UAVs. Indeed, due to the on-board energy constraints of UAVs, both the trajectory optimization and the power allocation can significantly save the energy to improve the energy efficiency. The joint trajectory optimization and power allocation problem is formulated as a mixed-integer non-convex optimization problem which is extremely difficult to solve. In order to reduce the computational complexity, we decompose the original optimization problem into two subproblems in terms of the trajectory optimization and power allocation. For the trajectory optimization subproblem, we model it as a Traveling Salesman Problem (TSP), and the PSO is adopted to solve it. When the trajectory variables are fixed, the power allocation subproblem is still difficult to tackle due to its nonconvexity and large scale. Firstly, we present a kind of centralized algorithm in which the DC (difference of two convex functions) algorithm is applied to optimize it, and then a distributed algorithm based on auxiliary variables is proposed to reduce the signaling overhead and computational complexity. The simulation results demonstrate the effectiveness of the proposed joint trajectory optimization and power allocation algorithm for the cell-free CSUN.INDEX TERMS Cell-free, satellite-UAV network, power allocation, NOMA.

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Section: Introductionmentioning

confidence: 99%

Trajectory Optimization and Power Allocation for Cell-Free Satellite-UAV Internet of Things

Wang

2023

IEEE Access

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“…The emergence of these latency-sensitive and compute-intensive applications, as well as the growth of maritime activities, has greatly improved the demand for maritime wireless communication. However, the satellite communication systems and high frequency/very high frequency (HF/VHF) communications used in traditional maritime communication networks have certain limitations [ 5 , 6 ]. Although satellite communications have a wide coverage area, they also have disadvantages such as high cost and large transmission delay.…”

Section: Introductionmentioning

confidence: 99%

Altitude Optimization and Task Allocation of UAV-Assisted MEC Communication System

Huang

Zhang

2022

Sensors

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Unmanned aerial vehicles (UAVs) are widely used in wireless communication systems due to their flexible mobility and high maneuverability. The combination of UAVs and mobile edge computing (MEC) is regarded as a promising technology to provide high-quality computing services for latency-sensitive applications. In this paper, a novel UAV-assisted MEC uplink maritime communication system is proposed, where an MEC server is equipped on UAV to provide flexible assistance to maritime user. In particular, the task of user can be divided into two parts: one portion is offloaded to UAV and the remaining portion is offloaded to onshore base station for computing. We formulate an optimization problem to minimize the total system latency by designing the optimal flying altitude of UAV and the optimal task allocation ratio. We derive a semi closed-form expression of the optimal flying altitude of UAV and a closed-form expression of the optimal task allocation ratio. Simulation results demonstrate the precision of the theoretical analyses and show some interesting insights.

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Channel Allocation for Mega LEO Satellite Constellations in the MEO–LEO Networked Telemetry System

Zeng

Zhan

Xie

2023

IEEE Internet Things J.

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Joint Power and Channel Allocation for Safeguarding Cognitive Satellite-UAV Networks

Cited by 5 publications

References 12 publications

Trajectory Optimization and Power Allocation for Cell-Free Satellite-UAV Internet of Things

Trajectory Optimization and Power Allocation for Cell-Free Satellite-UAV Internet of Things

Altitude Optimization and Task Allocation of UAV-Assisted MEC Communication System

Channel Allocation for Mega LEO Satellite Constellations in the MEO–LEO Networked Telemetry System

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