Joint Optimization of Relay Deployment, Channel Allocation, and Relay Assignment for UAVs-Aided D2D Networks

Zhong, Xijian; Guo, Yan; Li, Ning; Chen, Yancheng

doi:10.1109/tnet.2020.2970744

Cited by 89 publications

(66 citation statements)

References 48 publications

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“…where I 1 and I 2 are given in (15) and (16), as shown at the bottom of the page, respectively, with…”

Section: Outage Probability Analysis a Outage Probability Of Rementioning

confidence: 99%

“…Specifically, the authors investigated the secrecy energy efficiency maximization problem of that relaying system, where a high-mobility UAV flies at a fixed altitude from a given initial location to a final location to assists forwarding confidential information. The UAV-aided wireless communication systems with multiple single-antenna UAVs were studied in [15]- [17]. These UAVs acted as the relays for two-hop communication [15], [16] or multi-hop communication [17].…”

Section: Introductionmentioning

confidence: 99%

“…The UAV-aided wireless communication systems with multiple single-antenna UAVs were studied in [15]- [17]. These UAVs acted as the relays for two-hop communication [15], [16] or multi-hop communication [17]. However, the major issue of these works is that controlling many UAVs simultaneously may be very difficult and consumes much energy.…”

Section: Introductionmentioning

confidence: 99%

“…• Unlike previous studies on UAV-assisted wireless communication systems having only uplink [3], [18], [19] or downlink [6], [11], [13], or multiple UAV with single antenna [15]- [17], this papers proposes and analyzes an UAV-assisted NOMA relay system where a mobile multi-antenna UAV participates in signal forwarding of two source−destination pairs.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Outage Performance of Multi-Antenna Mobile UAV-Assisted NOMA Relay Systems Over Nakagami-m Fading Channels

2020

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“…where I 1 and I 2 are given in (15) and (16), as shown at the bottom of the page, respectively, with…”

Section: Outage Probability Analysis a Outage Probability Of Rementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Outage Performance of Multi-Antenna Mobile UAV-Assisted NOMA Relay Systems Over Nakagami-m Fading Channels

2020

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“…Thus, the UAV relays are responsible for providing wireless connectivity for remote users in adversarial environments, such as natural disaster recovery, military operation, rescue operation, etc. Moreover, UAV relays can be deployed to collect or disseminate information [4], [5]. Collecting or disseminating information is vital in various domains, such as periodic sensing or smart cities application.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks

et al. 2021

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The mobile relaying technique is a critical enhancing technology in wireless communications due to a higher chance of supporting the remote user from the base station (BS) with better service quality. This paper investigates energy-efficient (EE) mobile relaying networks mounted on the unmanned aerial vehicle (UAV) while the unknown adversaries try to intercept the legitimate link. We aim to optimize robust transmit power, both UAV and BS along, with relay hovering path, speed, and acceleration. The BS sends legitimate information, which is forwarded to the user by the relay. This procedure is defined as informationcausality-constraint (ICC). We jointly optimize the worst-case secrecy rate (WCSR) and UAV propulsion energy consumption (PEC) for a finite time horizon. We construct the BS-UAV, the UAV-user, and the UAV-adversary channel models. We apply the UAV PEC considering UAV speed and acceleration. We derive EE UAV relay-user maximization problem in the adversarial wireless networks at last. While the problem is non-convex, we propose an iterative and sub-optimal algorithm to optimize EE UAV relay with constraints, such as ICC, trajectory, speed, acceleration, and transmit power. First, we optimize both BS and UAV transmit power and hovering speed for known UAV path planning and acceleration. Using the optimal transmit power and speed, we obtain the optimal trajectory and acceleration. We compare our algorithm with existing algorithms and demonstrate the improved EE UAV relaying communication for our model. INDEX TERMS Energy-efficiency (EE), information-causality-constraint (ICC), propulsion energy consumption (PEC), worst case secrecy rate (WCSR).

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Maximization of instantaneous transmission rate in unmanned aerial vehicles‐supported self‐organized device‐to‐device network

Mondal

Hossain

2021

Int J Communication

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Summary Unmanned aerial vehicle (UAV)‐aided aerial base stations have emerged as a promising technique to provide rapid on‐demand wireless coverage for ground communicating devices in a geographical area. However, existing works on UAV‐enabled wireless communication systems overlook optimal deployment of UAVs under quality of service (QoS)‐aware device‐to‐device (D2D) communication. Therefore, this work proposes a UAV‐supported self‐organized device‐to‐device (USSD2D) network that employs multiple UAVs as relays for reliable D2D data transmission. The aim is to maximize the total instantaneous transmission rate of the USSD2D network by jointly optimizing devices' association with UAV, UAVs' channel selection, and their deployed location under signal‐to‐interference‐noise ratio (SINR) threshold. As this joint optimization problem is nonconvex and combinatorial, the formulated problem is transformed into a Markov decision process (MDP) that effectively splits up it into three individual optimization subproblems: devices association, UAVs' channel selection indicator, and UAVs' location at each instance. Finally, a reinforcement learning (RL) based on a low‐complexity iterative state–action–reward–state–action (SARSA) algorithm is developed to update UAVs' policy to solve this formulated problem. UAVs adopt the system parameters according to the current state and corresponding action to maximize the generated long‐term discounted reward under the current policy without prior knowledge about the environment. Numerical results validate the proposed approaches and provide various insights on optimal UAV deployment. This investigation demonstrates that the total instantaneous transmission rate of the USSD2D network can be improved by 75.25%, 51.31%, and 13.96% with respect to RS‐FORD, ES‐FIRD, and AOIV schemes, respectively.

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Joint Optimization of Relay Deployment, Channel Allocation, and Relay Assignment for UAVs-Aided D2D Networks

Cited by 89 publications

References 48 publications

Outage Performance of Multi-Antenna Mobile UAV-Assisted NOMA Relay Systems Over Nakagami-m Fading Channels

Outage Performance of Multi-Antenna Mobile UAV-Assisted NOMA Relay Systems Over Nakagami-m Fading Channels

Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks

Maximization of instantaneous transmission rate in unmanned aerial vehicles‐supported self‐organized device‐to‐device network

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