Placement and Power Allocation for NOMA-UAV Networks

Liu, Xiaonan; Wang, Jingjing; Zhao, Nan; Chen, Yunfei; Zhang, Shun; Ding, Zhiguo; Yu, F. Richard

doi:10.1109/lwc.2019.2904034

Cited by 160 publications

(112 citation statements)

References 16 publications

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“…Authors in [28], considered a multi-user system, in which a single-antenna UAV-BS serves a large number of ground users by employing NOMA. In [29], the placement and power allocation were jointly optimized to improve the performance of the NOMA-UAV network. In [30], a UAV and BS cooperate to serve ground users simultaneously.…”

Section: A Related Workmentioning

confidence: 99%

“…where e k = p r h k h r p 1 + p r h k + (p 1 + p 2 )h r + 1, and f = p r h 1 + (p 1 + p 2 )h r + 1. According to Lemma 2, the second logarithmic function of second equality in (32) is in the form of the difference of two concave functions as (29). For the first logarithmic function at second equality of (32), we subtract p 2 h r from the numerator and denominator to approximate it with a DC function as (29).…”

Section: Lemma 4 the Sum-rate Of The Two Vehicles Can Be Approximatementioning

confidence: 99%

“…According to Lemma 2, the second logarithmic function of second equality in (32) is in the form of the difference of two concave functions as (29). For the first logarithmic function at second equality of (32), we subtract p 2 h r from the numerator and denominator to approximate it with a DC function as (29). With the same procedure, the sum-rate at m = 2 can be approximated in the form of a DC function as (30).…”

Section: Lemma 4 the Sum-rate Of The Two Vehicles Can Be Approximatementioning

confidence: 99%

See 2 more Smart Citations

Trajectory Design and Power Allocation for Drone-Assisted NR-V2X Network With Dynamic NOMA/OMA

Abbasi

Yanıkömeroğlu

Ebrahimi

et al. 2020

IEEE Trans. Wireless Commun.

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In this paper, we find trajectory planning and power allocation for a vehicular network in which an unmanned-aerialvehicle (UAV) is considered as a relay to extend coverage for two disconnected far vehicles. We show that in a two-user network with an amplify-and-forward (AF) relay, non-orthogonalmultiple-access (NOMA) always has better or equal sum-rate in comparison to orthogonal-multiple-access (OMA) at high signalto-noise-ratio (SNR) regime. However, for the cases where i) base station (BS)-to-relay link is weak, or ii) two users have similar links, or iii) BS-to-relay link is similar to relay-to-weak user link, applying NOMA has negligible sum-rate gain. Hence, due to the complexity of successive-interference-cancellation (SIC) decoding in NOMA, we propose a dynamic NOMA/OMA scheme in which OMA mode is selected for transmission when applying NOMA has only negligible gain. Also, we show that OMA always has better min-rate than NOMA at high SNR regime. Further, we formulate two optimization problems which maximize the sum-rate and min-rate of the two vehicles. These problems are non-convex, and hence we propose an iterative algorithm based on alternating-optimization (AO) method which solves trajectory and power allocation sub-problems by successive-convexapproximation (SCA) and difference-of-convex (DC) methods, respectively. Finally, the above-mentioned performance is confirmed by simulations.

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Section: A Related Workmentioning

confidence: 99%

Section: Lemma 4 the Sum-rate Of The Two Vehicles Can Be Approximatementioning

confidence: 99%

Section: Lemma 4 the Sum-rate Of The Two Vehicles Can Be Approximatementioning

confidence: 99%

See 1 more Smart Citation

Trajectory Design and Power Allocation for Drone-Assisted NR-V2X Network With Dynamic NOMA/OMA

Abbasi

Yanıkömeroğlu

Ebrahimi

et al. 2020

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

show abstract

“…Bor-Yaliniz et al 14 maximize the number of users covered by a single ABS by finding an efficient three-dimensional placement (3DP) for the ABS. Liu et al 15 consider the problem of ABS placement and resource allocation adopting nonorthgonal multiple access as the transmission technology. They first optimize the location of the ABS is first optimized to minimize the path loss of the channels between ABSs to users.…”

Section: Related Workmentioning

confidence: 99%

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Azizi

Mokari

2019

Trans Emerging Tel Tech

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In this paper, a novel method for joint resource allocation, three-dimensional placement, and user association as a predominant problem in the internet of things (IoTs) networks is proposed. We consider two kinds of channel models for the links between users and aerial base stations (ABSs), namely (a) line of sight (LoS) model and (b) generalized model. In the LoS case, all the ABSs should establish LoS communications path toward IoT users. In the generalized case, the ABSs channels toward the IoT users could be LoS or nonline of sight. We propose four different scenarios, namely interference-free (IF)-LoS, IF-Generalized, interference-included (II)-LoS, and II-Generalized. The IF-LoS and IF-Generalized cases consider subcarrier and modulation order as the resources while the II-LoS and II-Generalized cases consider transmit power, subcarrier, and modulation order as the resources. Our objective function is minimizing the overall transmit power of the IoT users while satisfying some quality of service constraints in the uplink. To solve the resulting nonconvex optimization problem, we convert the main problem with high complexity into the subproblems with low complexities. We compare the performance of our joint proposed scenario with other joint and disjoint cases for the IF-LoS, IF-Generalized, II-LoS, and II-Generalized cases. Moreover, we evaluate the performance of the proposed schemes for different numbers of ABSs, environment types, target areas, and numbers of IoT users.Trans Emerging Tel Tech. 2019;30:e3632.wileyonlinelibrary.com/journal/ett

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“…In [27], Zhao et al jointly optimized the UAV trajectory and precoding vectors at the BS using NOMA to maximize the sum rate in UAV-assisted NOMA cellular networks. The joint optimization of placement and PA for NOMA based UAV networks was studied by Liu et al in [28]. Focusing on cellular-connected UAV networks, a novel cooperative NOMA scheme was proposed by Mei and Zhang in [29] by utilizing existing backhauls among BSs to realize interference cancellation, where the weighted sum rate of UAV and ground users is maximized by jointly optimizing the UAV's rate and PA over multiple resource blocks.…”

Section: Introductionmentioning

confidence: 99%

Uplink Precoding Optimization for NOMA Cellular-Connected UAV Networks

Pang

Gui

Zhao

et al. 2020

IEEE Trans. Commun.

Self Cite

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Unmanned aerial vehicles (UAVs) are playing an important role in wireless networks, due to their cost effectiveness and flexible deployment. Particularly, integrating UAVs into existing cellular networks has great potential to provide high-rate and ultra-reliable communications. In this paper, we investigate the uplink transmission in a cellular network from a UAV using non-orthogonal multiple access (NOMA) and from ground users to base stations (BSs). Specifically, we aim to maximize the sum rate of uplink from UAV to BSs in a specific band as well as from the UAV's co-channel users to their associated BSs via optimizing the precoding vectors at the multi-antenna UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the UAV-connected BSs, but also to the BSs associated with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the transmission rate requirements is formulated, which is non-convex. Thus, we introduce auxiliary variables and apply approximations based on the first-order Taylor expansion to convert it into a second-order cone programming. Accordingly, an iterative algorithm is designed to obtain the solution to the problem with low complexity. Numerical results are presented to demonstrate the effectiveness of our proposed scheme.

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Placement and Power Allocation for NOMA-UAV Networks

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Cited by 160 publications

References 16 publications

Trajectory Design and Power Allocation for Drone-Assisted NR-V2X Network With Dynamic NOMA/OMA

Trajectory Design and Power Allocation for Drone-Assisted NR-V2X Network With Dynamic NOMA/OMA

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Uplink Precoding Optimization for NOMA Cellular-Connected UAV Networks

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