Joint Trajectory and Precoding Optimization for UAV-Assisted NOMA Networks

Zhao, Nan; Pang, Xiaowei; Li, Zan; Chen, Yunfei; Li, Feng; Ding, Zhiguo; Alouini, Mohamed‐Slim

doi:10.1109/tcomm.2019.2895831

Cited by 288 publications

(156 citation statements)

References 42 publications

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“…Proof. Following the similar procedure in Appendix D, with interchanging M f w with M o w , we can obtain the desired result in (33). Thus, the proof is complete.…”

Section: Corollary 3 For the Nlos Scenario The Laplace Transform Ofmentioning

confidence: 67%

Exploiting NOMA for UAV Communications in Large-Scale Cellular Networks

Hou

Liu

Song

et al. 2019

IEEE Trans. Commun.

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This paper advocates a pair of strategies in non-orthogonal multiple access (NOMA) in unmanned aerial vehicles (UAVs) communications, where multiple UAVs play as new aerial communications platforms for serving terrestrial NOMA users. A new multiple UAVs framework with invoking stochastic geometry technique is proposed, in which a pair of practical strategies are considered: 1) the UAV-centric strategy for offloading actions and 2) the user-centric strategy for providing emergency communications.In order to provide practical insights for the proposed NOMA assisted UAV framework, an imperfect successive interference cancelation (ipSIC) scenario is taken into account. For both UAV-centric strategy and user-centric strategy, we derive new exact expressions for the coverage probability. We also derive new analytical results for orthogonal multiple access (OMA) for providing a benchmark scheme. The derived analytical results in both user-centric strategy and UAV-centric strategy explicitly indicate that the ipSIC coefficient is a dominant component in terms of coverage probability. Numerical results are provided to confirm that i) for both user-centric strategy and UAV-centric strategy, NOMA assisted UAV cellular networks is capable of outperforming OMA by setting power allocation factors and targeted rate properly; and ii) the coverage probability of NOMA assisted UAV cellular framework is affected to a large extent by ipSIC coefficient, target rates and power allocations factors of paired NOMA users. Index TermsNon-orthogonal multiple access, stochastic geometry, unmanned aerial vehicles. Regarding the literature of UAV networks, early research contributions have studied the performance of single UAV or multiple UAVs networks. Mozaffari et al. [3] proposed a UAV assisted underlaid D2D network with LoS probability, which depends on the height of the UAV, the horizontal distance between the UAV and users, the carrier frequency and type of environment. In the case that LoS exists, a fixed LoS coefficient, e.g., an extra 20dB attenuation, is the dominant component of small-scale fading channels. Note that the proposed model in [3], [4] is a practical model for implementation. For mathematically tractable, the distinctive channel characteristics for UAV networks were investigated in [13], where different types of small-scale fading channels, i.e., Loo model, Rayleigh model, Nakagami-m model, Rician model and Werbull model, were summarized to demonstrate the channel propagation of UAV networks. The air-to-air channel characterization in [14], studied the influence of the altitude-dependent Rician K factor. This work indicated that the impact of the ground reflected multi-path fading reduces with increasing UAV altitude. Jiang et al. [15] proposed a UAV assisted ground-to-air network, where Rician channels are used for evaluating strong LoS components between UAV and ground users. It is also worth noting that Rayleigh fading channel, which is a well-known model in scattering environment, can be also used to model the UAV ch...

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“…Proof. Following the similar procedure in Appendix D, with interchanging M f w with M o w , we can obtain the desired result in (33). Thus, the proof is complete.…”

Section: Corollary 3 For the Nlos Scenario The Laplace Transform Ofmentioning

confidence: 67%

Exploiting NOMA for UAV Communications in Large-Scale Cellular Networks

Hou

Liu

Song

et al. 2019

IEEE Trans. Commun.

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“…(7a) indicates that each UAV needs to provide illumination to meet the illumination threshold of each user j. (7b) indicates that the transmit power of UAV i should satisfy the data rate requirements of its associated users from (6). (7c) and (7d) imply that each user can only associate with one UAV at each time slot.…”

Section: B Problem Formulationmentioning

confidence: 99%

Gated Recurrent Units Learning for Optimal Deployment of Visible Light Communications Enabled UAVs

Wang

Chen

Yang

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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In this paper, the problem of optimizing the deployment of unmanned aerial vehicles (UAVs) equipped with visible light communication (VLC) capabilities is studied. In the studied model, the UAVs can predict the illumination distribution of a given service area and determine the user association with the UAVs to simultaneously provide communications and illumination. However, ambient illumination increases the interference over VLC links while reducing the illumination threshold of the UAVs.Therefore, it is necessary to consider the illumination distribution of the target area for UAV deployment optimization. This problem is formulated as an optimization problem, which jointly optimizes UAV deployment, user association, and power efficiency while meeting the illumination and communication requirements of users. To solve this problem, an algorithm that combines the machine learning framework of gated recurrent units (GRUs) with convolutional neural networks (CNNs) is proposed. Using GRUs and CNNs, the UAVs can model the long-term historical illumination distribution and predict the future illumination distribution. Based on the prediction of illumination distribution, the optimization problem becomes nonconvex and is then solved using a low-complexity, iterative physical relaxation algorithm.The proposed algorithm can find the optimal UAV deployment and user association to minimize the total transmit power. Simulation results using real data from the Earth observations group (EOG) at NOAA/NCEI show that the proposed approach can achieve up to 64.6% reduction in total transmit power compared to a conventional optimal UAV deployment that does not consider the illumination Y. Wang and T. Luo are with the Beijing 2 distribution and user association. The results also show that UAVs must hover at areas having strong illumination, thus providing useful guidelines on the deployment of VLC-enabled UAVs. Index TermsVisible light communication, unmanned aerial vehicles, drones, machine learning, gated recurrent units, convolutional neural networks, energy efficiency. I. INTRODUCTIONDeploying unmanned aerial vehicles (UAVs) as flying base stations (BSs) for wireless networking is a flexible and cost-effective approach to providing on-demand communications [2]-[6]. However, for tomorrow's ultra dense wireless networks that encompass a large number of ground BSs, UAVs may not have enough radio frequency (RF) resources to service ground users. Moreover, UAVs deployed as aerial BSs using RF will interfere with ground devices, hence significantly affecting the performance of the ground network. In addition, the limited energy will restrict the applicability of UAVs using RF resource to provide high-speed communication services for ground users. These challenges can be addressed by equipping UAVs with visible light communication (VLC) capabilities [7]. Indeed, VLC has recently attracted attention due to its large license-free bandwidth and high energy efficiency. For instance, a VLC system that uses light-emitting diodes (LEDs) to t...

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“…Furthermore, a pair of NOMA assisted caching strategies were proposed to emphasize the wireless caching [10]. To better understand NOMA assisted unmaned aerial vehicle networks, the authors of [11,12] have evaluated the performance in terms of both outage probability and fly trajectory.…”

Section: Introductionmentioning

confidence: 99%

Outage Behaviors of NOMA-Based Satellite Network Over Shadowed-Rician Fading Channels

Yue

Liu

Yao

et al. 2020

IEEE Trans. Veh. Technol.

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This paper investigates the application of nonorthogonal multiple access (NOMA) to satellite communication network over Shadowed-Rician fading channels. The impact of imperfect successive interference cancellation (ipSIC) on NOMAbased satellite network is taken into consideration from the perspective of practical scenarios. We first derive new exact expressions of outage probability for the p-th terrestrial user and provide the corresponding asymptotic analysis results. The diversity order of zero and p are achieved by the p-th terrestrial user with ipSIC and perfect successive interference cancellation (pSIC), respectively. Finally, the presented simulation results show that: 1) On the condition of pSIC, the outage behaviors of NOMA-based satellite network are superior to that of orthogonal multiple access; 2) With the value of residual interference increasing, the outage performance of terrestrial users with ipSIC is becoming worse seriously; and 3) Infrequent light shadowing of Shadowed-Rician fading brings the better outage probability compared to frequent heavy and average shadowing.

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Joint Trajectory and Precoding Optimization for UAV-Assisted NOMA Networks

Cited by 288 publications

References 42 publications

Exploiting NOMA for UAV Communications in Large-Scale Cellular Networks

Exploiting NOMA for UAV Communications in Large-Scale Cellular Networks

Gated Recurrent Units Learning for Optimal Deployment of Visible Light Communications Enabled UAVs

Outage Behaviors of NOMA-Based Satellite Network Over Shadowed-Rician Fading Channels

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