NOMA-based UAV-aided networks for emergency communications

Feng, Wanmei; Tang, Jie; Zhao, Nan; Fu, Yuli; Zhang, Xiu Yin; Cumanan, Kanapathippillai; Wong, Kai-Kit

doi:10.23919/jcc.2020.11.005

Cited by 49 publications

(33 citation statements)

References 15 publications

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“…Herein, the authors propose a novel power allocation strategy to maintain a balance between the system throughput and performance fairness. [27] proposes a framework for NOMA based UAV aided network to achieve high spectral efficiency and massive connections during emergency situation. The paper considers both single UAV and multi-UAV assisted networks and develops a joint trajectory and power optimization scheme to provide reliable services for both the cases.…”

Section: A Related Workmentioning

confidence: 99%

Multi-UAV Assisted IoT NOMA Uplink Communication System for Disaster Scenario

Barick

Singhal

2022

IEEE Access

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Unmanned aerial vehicle (UAV) communication has become a prominent technology that can effectively assist in IoT systems. The inherent features of UAV such as mobility, flexibility, and fast deployment make it preferable for emergency Internet of Things (IoT) applications. In this paper, we consider a multi-UAV assisted wireless network to support uplink communication for IoT devices distributed over a disaster area. The network involves two types of UAVs: sector UAV (SU) and anchor UAV (AU). The SU hovers at a fixed height over the sector around the temporary base station (TBS), collects the information from the respective IoT devices and relays them to the TBS via AU. The AU revolves continuously around the TBS and relays the information between the SUs and TBS periodically. We aim to improve the uplink capacity of the system. To achieve this, we employ non-orthogonal multiple access (NOMA), where we jointly optimize the positions of SUs and the power control of IoT devices. We propose a two-step approach to solve this. First, we optimize the position of SU in each sector by minimizing the sum distances of SU from the respective IoT devices. Then, by considering the optimal SU location, we optimize the transmit power of IoT devices using Lagrange dual method. Finally, the experimental results show that the proposed scheme improves the system capacity by 22% compared to the state-of-the-art schemes.INDEX TERMS UAV network, Internet-of-Things, uplink transmission, NOMA, system capacity.

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Section: A Related Workmentioning

confidence: 99%

Multi-UAV Assisted IoT NOMA Uplink Communication System for Disaster Scenario

Barick

Singhal

2022

IEEE Access

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“…Likewise, at very high v XZ and/or f c and/or τ , ρ XZ tends to 0, yielding severe channel time variations, in which the estimated CSI is completely uncorrelated with the actual one. Also, it worth mentioning that J 0 (x) in (6), with x = 2πv XZ fcτ c , is a decreasing function of v XZ and/or f c and/or τ over x ∈ [0, x 0 ] , with x 0 = 3.8317 being the function's minima that can be found numerically by retrieving the first zero of (J 0 (x)) .…”

Section: E Notationsmentioning

confidence: 99%

“…Nonetheless, despite the aforesaid features and applications, guaranteeing a fair functioning of such IoT networks is challenging in underserved areas (e.g., deserts, mountains), or in disaster zones non-covered by wireless cellular infrastructure [3], [6].…”

Section: Introductionmentioning

confidence: 99%

On the Physical Layer Security of a Dual-Hop UAV-based Network in the Presence of per-hop Eavesdropping and Imperfect CSI

Illi¹,

Qaraqe²,

Bouanani³

et al. 2022

Preprint

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In this paper, the physical layer security of a dualhop unmanned aerial vehicle-based wireless network, subject to imperfect channel state information (CSI) and mobility effects, is analyzed. Specifically, a source node (S) communicates with a destination node (D) through a decode-and-forward relay (R), in the presence of two wiretappers (E1, E2) independently trying to compromise the two hops. Furthermore, the transmit nodes (S, R) have a single transmit antenna, while the receivers (R, D, E1, E2) are equipped with multiple receive antennas. Based on the per-hop signal-to-noise ratios (SNRs) and correlated secrecy capacities' statistics, a closed-form expression for the secrecy intercept probability (IP) metric is derived, in terms of key system parameters. Additionally, asymptotic expressions are revealed for two scenarios, namely (i) mobile nodes with imperfect CSI and (ii) static nodes with perfect CSI. The results show that a zero secrecy diversity order is manifested for the first scenario, due to the presence of a ceiling value of the average SNR, while the IP drops linearly at high average SNR in the second one, where the achievable diversity order depends on the fading parameters and number of antennas of the legitimate links/nodes. Furthermore, for static nodes, the system can be castigated by a 15 dB secrecy loss at IP= 3×10 −3 , when the CSI imperfection power raises from 0 to 10 −3 . Lastly, the higher the legitimate nodes' speed, carrier frequency, delay, and/or relay's decoding threshold SNR, the worse is the system's secrecy. Monte Carlo simulations endorse the derived analytical results.

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“…Simulation results demonstrated that the combination of SWIPT and NOMA could further improve the EE of the communication network. Based on the prior works on NOMA-enabled wireless networks, the applications of UAVs within NOMA networks can further improve the system throughput since they can shorten the transmission distance and increase the channel gain [17]- [19]. In [17], the authors investigated the time sharing (TS) NOMA networks, and developed a resource allocation algorithm to maximize the EE of the UAV-TS-NOMA networks.…”

Section: Introductionmentioning

confidence: 99%

“…To guarantee the quality of service (QoS), the authors developed a data collection optimization algorithm using the generalized benders decomposition methods. The authors in [19] studied the UAV-assisted NOMA networks for emergency communications. Firstly, a deep-Q-learning-based scheme was proposed to maximize the sum rate of the UAV-enabled uplink NOMA networks.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficiency Optimization for D2D Communications Underlaying UAV-Assisted Industrial IoT Networks With SWIPT

Feng

Tang

et al. 2023

IEEE Internet Things J.

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The industrial Internet of Things (IIoT) has been viewed as a typical application for the fifth generation (5G) mobile networks. This paper investigates the energy efficiency (EE) optimization problem for the device-to-device (D2D) communications underlaying unmanned aerial vehicles (UAVs)-assisted IIoT networks with simultaneous wireless information and power transfer (SWIPT). We aim to maximize the EE of the system while satisfying the constraints of transmission rate and transmission power budget. However, the designed EE optimization problem is non-convex involving joint optimization of the UAV's location, beam pattern, power control and time scheduling, which is difficult to tackle directly. To solve this problem, we present a joint UAV location and resource allocation algorithm to decouple the original problem into several sub-problems and solve them sequentially. Specifically, we first apply the Dinkelbach method to transform the fraction problem to a subtractive-form one, and propose a mulitiobjective evolutionary algorithm based on decomposition (MOEA/D) based algorithm to optimize the beam pattern. We then optimize UAV's location and power control using the successive convex optimization techniques. Finally, after solving the above variables, the original problem can be transformed into a single-variable problem with respect to the charging time, which is linear and can be tackled directly. Numerical results verify that significant EE gain can be obtained by our proposed algorithm as compared to the benchmark schemes.

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NOMA-based UAV-aided networks for emergency communications

Cited by 49 publications

References 15 publications

Multi-UAV Assisted IoT NOMA Uplink Communication System for Disaster Scenario

Multi-UAV Assisted IoT NOMA Uplink Communication System for Disaster Scenario

On the Physical Layer Security of a Dual-Hop UAV-based Network in the Presence of per-hop Eavesdropping and Imperfect CSI

Energy-Efficiency Optimization for D2D Communications Underlaying UAV-Assisted Industrial IoT Networks With SWIPT

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