Sum Rate Maximization for UAV-Enabled Wireless Powered NOMA Systems
09 Aug 2020-pp 753-757
TL;DR: This paper considers the sum rate maximization problem of uplink non-orthogonal multiple access (NOMA) system with unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT).
Abstract: In this paper, we consider the sum rate maximization problem of uplink non-orthogonal multiple access (NOMA) system with unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT). The sum rate problem is a non-convex problem, which is difficult to handle directly because the energy harvesting time and position of UAV are coupled in the objective function. We propose an iterative algorithm to search the energy harvesting time and the position of UAV. The energy harvesting time problem is solved by the bisection search method. Then, the position optimization problem is solved by the quadratic transform method. Finally, based on the above two methods, we propose a two-tier iterative algorithm to jointly optimizing the energy harvesting time and position of the UAV. Simulation results show that the proposed algorithm has a better performance compared with the benchmark algorithms.
Citations
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TL;DR: In this paper, the authors considered a UAV uplink communication system based on NOMA, in which the UAV receives information from the ground users with a certain flying altitude and formulated an optimization problem that maximizes the sum throughput subject to each user's transmit power constraint and their corresponding minimum transmission rate requirement.
Abstract: In order to fully utilize the spectrum resources, this work considers a unmanned aerial vehicle (UAV) uplink communication system based on non-orthogonal multiple access technology (NOMA), in which the UAV receives information from the ground users with a certain flying altitude. As an initial study, we consider a simplified setup with two ground users to draw some insightful results. Explicitly, we first formulate an optimization problem that maximizes the sum throughput subject to each user's transmit power constraint and their corresponding minimum transmission rate requirement. Then, both the optimal transmit power and UAV's deployment location are derived with the aid of employing the Karush-Kuhn-Tucher (KKT) conditions. Simulation results show that the proposed UAV's deployment scheme with the users' power allocation can achieve a higher sum throughput compared with two existing benchmark schemes.
1 citations
19 Oct 2022
TL;DR: In this article , the authors proposed an iterative algorithm to solve the problem by using the block coordinated descent (BCD) technique and quadratic transform algorithm, which achieves higher sum rate than the other schemes.
Abstract: This paper considers a backscatter communication (BC) system, which is based on the non-orthogonal multiple access (NOMA) protocol and assisted by a full-duplex unmanned aerial vehicle (UAV). To improve the communication quality of this NOMA-based system, we increase the number of backscatter devices (BDs) and maximize the sum rate by optimizing the reflection coefficient (RC) of BDs and the location of the UAV. As the sum rate problem is a non-convex problem, we propose an iterative algorithm to solve the problem by using the block coordinated descent (BCD) technique and quadratic transform algorithm. The RC problem is solved by monotonicity. Then, the location problem is solved by the quadratic transform algorithm. Finally, simulation results demonstrate that the proposed algorithm achieves higher sum rate than the other schemes.
1 citations
18 Aug 2021
TL;DR: In this article, the authors decompose the non-convex sum rate maximization problem into two subproblems: position optimization problem and power allocation problem, and then the closed-form PA algorithm is used to further maximize the sum rate under a fixed UAV's location obtained by GA.
Abstract: Unmanned aerial vehicle (UAV) network based on non-orthogonal multiple access (NOMA) jointly optimizes the location and power allocation (PA) of UAV to achieve better sum rate. However, this non-convex sum rate maximization problem is difficult to solve. Therefore, we decompose this non-convex problem into two sub-problems. First, genetic algorithm (GA) is used to solve the position optimization problem, which is equivalent to sum rate maximization problem. Then, the closed-form PA algorithm is used to further maximize the sum rate under a fixed UAV’s location obtained by GA. Compared with PA algorithm with geometric center placement, numerical results demonstrate the effectiveness of the proposed algorithm.
19 Oct 2022
TL;DR: In this article , a backscatter communication (BC) system based on the NOMA protocol and assisted by a full-duplex unmanned aerial vehicle (UAV) is considered.
Abstract: This paper considers a backscatter communication (BC) system, which is based on the non-orthogonal multiple access (NOMA) protocol and assisted by a full-duplex unmanned aerial vehicle (UAV). To improve the communication quality of this NOMA-based system, we increase the number of backscatter devices (BDs) and maximize the sum rate by optimizing the reflection coefficient (RC) of BDs and the location of the UAV. As the sum rate problem is a non-convex problem, we propose an iterative algorithm to solve the problem by using the block coordinated descent (BCD) technique and quadratic transform algorithm. The RC problem is solved by monotonicity. Then, the location problem is solved by the quadratic transform algorithm. Finally, simulation results demonstrate that the proposed algorithm achieves higher sum rate than the other schemes.
TL;DR: In this article , the authors present the latest advances in WPT UAV methodologies and related energy-centric services, spanning all the way from the communications aspects deep in the small and large scale deployments, up to the operational and applications aspects.
References
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TL;DR: The concept of software defined multiple access (SoDeMA) is proposed, which enables adaptive configuration of available multiple access schemes to support diverse services and applications in future 5G networks.
Abstract: The increasing demand of mobile Internet and the Internet of Things poses challenging requirements for 5G wireless communications, such as high spectral efficiency and massive connectivity. In this article, a promising technology, non-orthogonal multiple access (NOMA), is discussed, which can address some of these challenges for 5G. Different from conventional orthogonal multiple access technologies, NOMA can accommodate much more users via nonorthogonal resource allocation. We divide existing dominant NOMA schemes into two categories: power-domain multiplexing and code-domain multiplexing, and the corresponding schemes include power-domain NOMA, multiple access with low-density spreading, sparse code multiple access, multi-user shared access, pattern division multiple access, and so on. We discuss their principles, key features, and pros/cons, and then provide a comprehensive comparison of these solutions from the perspective of spectral efficiency, system performance, receiver complexity, and so on. In addition, challenges, opportunities, and future research trends for NOMA design are highlighted to provide some insight on the potential future work for researchers in this field. Finally, to leverage different multiple access schemes including both conventional OMA and new NOMA, we propose the concept of software defined multiple access (SoDeMA), which enables adaptive configuration of available multiple access schemes to support diverse services and applications in future 5G networks.
2,512 citations
"Sum Rate Maximization for UAV-Enabl..." refers background in this paper
...Non-orthogonal multiple access (NOMA), as an emerging technology, can solve many challenges of 5G through non-orthogonal resource allocation [1]....
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TL;DR: In this article, a cooperative NOMA scheme is proposed, where users with better channel conditions have prior information about the messages of other users, and an approach based on user pairing is also proposed to reduce system complexity.
Abstract: Non-orthogonal multiple access (NOMA) has received considerable recent attention as a promising candidate for 5G systems. A key feature of NOMA is that users with better channel conditions have prior information about the messages of other users. This prior knowledge is fully exploited in this letter, where a cooperative NOMA scheme is proposed. The outage probability and diversity order achieved by this cooperative NOMA scheme are analyzed, and an approach based on user pairing is also proposed to reduce system complexity.
1,104 citations
TL;DR: Numerical results show that by optimizing the trajectory of the relay and power allocations adaptive to its induced channel variation, mobile relaying is able to achieve significant throughput gains over the conventional static relaying.
Abstract: In this paper, we consider a novel mobile relaying technique, where the relay nodes are mounted on unmanned aerial vehicles (UAVs) and hence are capable of moving at high speed. Compared with conventional static relaying, mobile relaying offers a new degree of freedom for performance enhancement via careful relay trajectory design. We study the throughput maximization problem in mobile relaying systems by optimizing the source/relay transmit power along with the relay trajectory, subject to practical mobility constraints (on the UAV’s speed and initial/final relay locations), as well as the information-causality constraint at the relay. It is shown that for the fixed relay trajectory, the throughput-optimal source/relay power allocations over time follow a “staircase” water filling structure, with non-increasing and non-decreasing water levels at the source and relay, respectively. On the other hand, with given power allocations, the throughput can be further improved by optimizing the UAV’s trajectory via successive convex optimization. An iterative algorithm is thus proposed to optimize the power allocations and relay trajectory alternately. Furthermore, for the special case with free initial and final relay locations, the jointly optimal power allocation and relay trajectory are derived. Numerical results show that by optimizing the trajectory of the relay and power allocations adaptive to its induced channel variation, mobile relaying is able to achieve significant throughput gains over the conventional static relaying.
1,079 citations
"Sum Rate Maximization for UAV-Enabl..." refers background in this paper
...However energy harvesting (EH) is not considered in [5]–[8]....
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...The authors of [8] proposed a novel mobile relaying technology that maximizes the system throughput by optimizing transmit power of relay and trajectory of UAV....
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TL;DR: In this article, a quadratic transform technique is proposed for solving the multiple-ratio concave-convex FP problem, where the original nonconveX problem is recast as a sequence of convex problems.
Abstract: Fractional programming (FP) refers to a family of optimization problems that involve ratio term(s). This two-part paper explores the use of FP in the design and optimization of communication systems. Part I of this paper focuses on FP theory and on solving continuous problems. The main theoretical contribution is a novel quadratic transform technique for tackling the multiple-ratio concave–convex FP problem—in contrast to conventional FP techniques that mostly can only deal with the single-ratio or the max-min-ratio case. Multiple-ratio FP problems are important for the optimization of communication networks, because system-level design often involves multiple signal-to-interference-plus-noise ratio terms. This paper considers the applications of FP to solving continuous problems in communication system design, particularly for power control, beamforming, and energy efficiency maximization. These application cases illustrate that the proposed quadratic transform can greatly facilitate the optimization involving ratios by recasting the original nonconvex problem as a sequence of convex problems. This FP-based problem reformulation gives rise to an efficient iterative optimization algorithm with provable convergence to a stationary point. The paper further demonstrates close connections between the proposed FP approach and other well-known algorithms in the literature, such as the fixed-point iteration and the weighted minimum mean-square-error beamforming. The optimization of discrete problems is discussed in Part II of this paper.
840 citations
TL;DR: In this paper, a novel framework for UAV networks with massive access capability supported by NOMA is proposed, where stochastic geometry is adopted to model the positions of UAVs and ground users.
Abstract: This article proposes a novel framework for UAV networks with massive access capability supported by NOMA In order to better understand NOMA-enabled UAV networks, three case studies are carried out We first provide performance evaluation of NOMA-enabled UAV networks by adopting stochastic geometry to model the positions of UAVs and ground users Then we investigate the joint trajectory design and power allocation for static NOMA users based on a simplified 2D model of UAV flying around at fixed height As a further advance, we demonstrate the UAV placement issue with the aid of machine learning techniques when the ground users are roaming and the UAVs are capable of adjusting their positions in three dimensions accordingly With these case studies, we can comprehensively understand the UAV systems from fundamental theory to practical implementation
237 citations