Spectrum Sharing Planning for Full-Duplex UAV Relaying Systems With Underlaid D2D Communications

Wang, Haichao; Wang, Jinlong; Ding, Guoru; Chen, Jin; Li, Yuzhou; Han, Zhu

doi:10.1109/jsac.2018.2864375

Cited by 171 publications

(92 citation statements)

References 39 publications

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“…Otherwise, the backhaul power allocations are adjusted using the same procedure in (18). The two-stage backhaul power allocation update procedure exploits the transmission power upper bound of the IABdonor and assures that the inequality constraints of backhaul transmissions in (10a) are satisfied, which is critical for UAVassisted IAB scenarios.…”

Section: A Fixed-point Iteration Methods For Pamentioning

confidence: 99%

Interference Management in UAV-Assisted Integrated Access and Backhaul Cellular Networks

et al. 2019

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An integrated access and backhaul (IAB) network architecture can enable flexible and fast deployment of nextgeneration cellular networks. However, mutual interference between access and backhaul links, small inter-site distance and spatial dynamics of user distribution pose major challenges in the practical deployment of IAB networks. To tackle these problems, we leverage the flying capabilities of unmanned aerial vehicles (UAVs) as hovering IAB-nodes and propose an interference management algorithm to maximize the overall sum rate of the IAB network. In particular, we jointly optimize the user and base station associations, the downlink power allocations for access and backhaul transmissions, and the spatial configurations of UAVs. We consider two spatial configuration modes of UAVs: distributed UAVs and drone antenna array (DAA), and show how they are intertwined with the spatial distribution of ground users. Our numerical results show that the proposed algorithm achieves an average of 2.9× and 6.7× gains in the received downlink signal-to-interference-plus-noise ratio (SINR) and overall network sum rate, respectively. Finally, the numerical results reveal that UAVs cannot only be used for coverage improvement but also for capacity boosting in IAB cellular networks.Index Terms-3D localization, downlink, drone, drone antenna array (DAA), in-band, integrated access and backhaul (IAB), optimization, UAV.

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Section: A Fixed-point Iteration Methods For Pamentioning

confidence: 99%

Interference Management in UAV-Assisted Integrated Access and Backhaul Cellular Networks

et al. 2019

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“…Specifically, sub-problem 1 is a convex optimization problem as (23). With the assist of penalty term and SCA technique, sub-problem 2 is solved in a standard LP form as (29). With the introduction of slack variables, SCA technique and S-Procedure, sub-problem 3 is solved as a semidefinite programming problem as (44).…”

Section: Overall Algorithmmentioning

confidence: 99%

Robust Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks in the Presence of Jammers

Fan

Yang

et al. 2020

IEEE Access

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This paper investigates a multi-unmanned aerial vehicle (UAV) enabled wireless communication, where a number of ground nodes (GNs) are scheduled to communicate with UAVs in the presence of jammers with imperfect location information. Considering different quality of service (QoS) requirements for a wide range of applications, we aim to improve the minimum throughput, the average throughput, and the delay-constrained minimum throughput of all GNs, respectively, via the joint design of UAVs' trajectories, GNs' scheduling and power allocation. However, the formulated optimization problems are difficult to solve due to the non-convex and combinatorial nature. To overcome this difficulty, we propose two block coordinate descent (BCD) based algorithms to solve them sub-optimally with the aid of slack variables, successive convex approximation (SCA) technique and S-procedure. Numerical results show that our proposed algorithms outperforms the benchmark algorithms and offers a considerable gain in the view of different QoS requirements, giving a certain practical significance. INDEX TERMS UAV communications, trajectory optimization, anti-jamming, robust design, QoS requirement. egy of the UAV was proposed to enhance the system performance. However, without providing sequential trajectory, [25] and [26] explored little facility of UAV's maneuverability and flexibility. Thus, by taking spatial retreats into account, in [27] and [28], a trajectory optimization algorithm was investigated to combat jamming signals where the UAV would fly away from the jammers while executing communication tasks. In [29], the UAV's trajectory and communication resources were jointly designed to guarantee the coexistence with the jamming signals from the terrestrial D2D GNs. Nevertheless, these works assumed that jammers' location was perfectly known. Though a robust optimization method was studied in [30], where one UAV needed to maintain the communication quality in the presence of an adversarial jammer with uncertain location information, however, considered little about the joint optimization of trajectory and communication resources for multiple UAV. Particularly, in the multi-UAV enabled communication, the communication resources allocation for various UAV-GN pairs need to be tackled. In [31], a joint trajectory, power allocation and user scheduling algorithm was applied to mitigate the interference of system users. In [32], the UAV to UAV communication was investigated via joint trajectory and power optimization wherein the UAVs shared the same frequency. In [33] and [34], orthogonal frequency division multiple access (OFDMA) mode and time division multiple access (TDMA) mode were applied to avoid the interference of system users, respectively. Consequently, with the possible interference caused by system users, the jamming attacks from a adversarial jammer is more challenging in the multi-UAV enabled communication and has not been fully investigated. Moreover, wireless communication systems have gradually evolved to aim not only for hig...

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“…Therefore, in this paper, we study an untrusted UAV network. Since, with a proper selfinterference cancellation, full-duplex (FD) communications achieve a higher multiplexing gain than half-duplex (HD) communications, e.g., [16], FD communication is one of the key transmission techniques for 5G and beyond applications. We thus consider FD UAVs as well.…”

Section: B Problem Statementmentioning

confidence: 99%

Physical-Layer Security for Untrusted UAV-Assisted Full-Duplex Wireless Networks

Nuradha

Hemachandra

Samarasinghe

et al. 2019

2019 IEEE Globecom Workshops (GC Wkshps)

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The paper considers physical layer security (PLS) of an untrusted unmanned aerial vehicle (UAV) network, where a multitude of UAVs communicate in full-duplex (FD) mode. A source-based jamming (SBJ) scheme is exploited for secure communication without utilizing any external jammers. Firstly, the optimal power allocation between the confidential signal and the jamming signal is derived to maximize the secrecy rate of each link between the source and the destination. Then, the best UAV selection scheme is proposed to maximize the overall secrecy rate of the network. The corresponding secrecy outage probability (SOP) and the average secrecy rate (ASR) of the network are analyzed based on the proposed UAV selection and the optimal power allocation schemes. Asymptotic results are also obtained to derive the achievable diversity order. Results are validated through numerical evaluations while providing useful network design insights such as locations and altitudes of the UAVs.Index Terms-Full-duplex, optimal power allocation, physical layer security, source jamming, unmanned aerial vehicle (UAV).

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Spectrum Sharing Planning for Full-Duplex UAV Relaying Systems With Underlaid D2D Communications

Cited by 171 publications

References 39 publications

Interference Management in UAV-Assisted Integrated Access and Backhaul Cellular Networks

Interference Management in UAV-Assisted Integrated Access and Backhaul Cellular Networks

Robust Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks in the Presence of Jammers

Physical-Layer Security for Untrusted UAV-Assisted Full-Duplex Wireless Networks

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