Power Allocation for a Downlink Non-Orthogonal Multiple Access System

Wang, Chin-Liang; Chen, Jyun-Yu; Chen, Yi-Jhen

doi:10.1109/lwc.2016.2598833

Cited by 162 publications

(111 citation statements)

References 9 publications

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“…Note that we also apply the GP (Gradient Projection) algorithm (used in Ref. [12]) to solve problem (8), which can achieve almost the same sum rate as the proposed closedform solution in section 3.1. Nevertheless, the GP algorithm has a higher computational and implemen-tation complexity owing to the iterative mechanism and the fact that one convex problem needs to be solved in each iteration [12] .…”

Section: Simulation Resultsmentioning

confidence: 99%

“…With respect to NOMA in RF wireless communications, a number of studies have focused on devising power allocation strategies to enhance the system performance [7][8][9] . The max-min fairness based power allocation was studied in Ref.…”

Section: Introductionmentioning

confidence: 99%

“…Alternatively, the authors in Ref. [8] considered maximizing the sum rate of the NOMA system with two users. Moreover, a general power allocation was proposed in Ref.…”

Section: Introductionmentioning

confidence: 99%

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Optimal power allocation for downlink two-user non-orthogonal multiple access in visible light communication

Shen

et al. 2017

J. Commun. Inf. Netw.

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In this work, we consider employing the NOMA (Non-Orthogonal Multiple Access) technique in downlink VLC (Visible Light Communication) for performance enhancement. In particular, focusing on a typical NOMA scenario with two users, we optimize the power allocation strategies under both sum-rate maximization and max-min fairness criteria, where practical optical power and QoS (Quality of Service) constraints are included. As our main contribution, we achieve optimal power allocation solutions in semi-closed forms via mathematical analysis, which, to the best of our knowledge, have not been reported in literature. Simulation results demonstrate that NOMA can provide remarkable performance gains over OMA (Orthogonal Multiple Access) in the context of VLC downlinks.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal power allocation for downlink two-user non-orthogonal multiple access in visible light communication

Shen

et al. 2017

J. Commun. Inf. Netw.

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“…Thus, the optimization must guarantee the minimum rate requirements of each user and is missing in the work of Zhang et al Yang et al optimized the power allocation in two‐user NOMA system to guarantee quality of service (QoS) of each user. In the work of Wang et al, the problem of power allocation for sum rate maximization in a two‐user NOMA assisted downlink system was solved under constraints of limited power budget and per user rate requirements. The work of Wang et al was extended for NOMA based cognitive radio networks in the work of Zabetian et al The sum rate maximization was further investigated under joint optimization of power allocation and channel assignment in the works of Lei et al and Di et al The optimization to maximize the overall throughput enhances the system performance, however may result in unfair QoS provision for different users .…”

Section: Introductionmentioning

confidence: 99%

“…In the work of Wang et al, the problem of power allocation for sum rate maximization in a two‐user NOMA assisted downlink system was solved under constraints of limited power budget and per user rate requirements. The work of Wang et al was extended for NOMA based cognitive radio networks in the work of Zabetian et al The sum rate maximization was further investigated under joint optimization of power allocation and channel assignment in the works of Lei et al and Di et al The optimization to maximize the overall throughput enhances the system performance, however may result in unfair QoS provision for different users . Moreover, the nature of power allocation in NOMA may introduce an additional degree of unfairness and, thus, investigating the fair NOMA designs becomes more important .…”

Section: Introductionmentioning

confidence: 99%

On fair power optimization in nonorthogonal multiple access multiuser networks

Ali

Sidhu

Waqas

et al. 2018

Trans Emerging Tel Tech

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Nonorthogonal multiple access (NOMA) has been recognized as a key solution to fulfill the demands of 5G wireless communication. In this paper, our aim is to maximize the fairness in the data rates of different users in a multiuser NOMA system. We optimize the downlink transmission subject to minimum rate requirement of each user, limited power budget at the transmitter, and the successive interference cancelation constraint. First, we solve the problem for two‐user scenario where the nonconvex problem is transformed into a standard convex minimization problem and the duality theory is exploited to find the solution. The optimal power allocation is obtained from the Karush‐Kuhn‐Tucker (KKT) conditions, whereas the dual problem is solved via subgradient algorithm. As a next step, we consider the general multiuser optimization problem where more than two users can share the same channel under NOMA transmission. We design efficient solution techniques to solve the nonconvex optimization problem with sequential quadratic programming (SQP). Furthermore, two suboptimal low complexity solutions are also presented. We found that, under the proposed schemes, the fairness increases with increasing the available transmit power and decreases with the increasing the number of users. We show a complexity comparison of the dual‐based solution and the SQP algorithm. It is observed that power optimization through KKT conditions exhibits much lower computational complexity as compared to the SQP‐based solution.

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User scheduling and power allocation for nonfull buffer traffic in NOMA downlink systems

Gemici

Kara

Hökelek

et al. 2018

Int J Communication

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Nonorthogonal multiple access (NOMA) is one of the key technologies for 5G, where the system capacity can be increased by allowing simultaneous transmission of multiple users at the same radio resource. The most of the proportional fairness (PF)-based resource allocation studies for NOMA systems assumes full buffer traffic model, while the traffic in real-life scenarios is generally nonfull buffer. In this paper, we propose User Demand-Based Proportional Fairness (UDB-PF) and Proportional User Satisfaction Fairness (PUSF) algorithms for user scheduling and power allocation in NOMA downlink systems when traffic demands of the users are limited and time-varying. UDB-PF extends the PF-based scheduling by allocating optimum power levels towards satisfying the traffic demand constraints of user pair in each resource block. The objective of PUSF is to maximize the network-wide user satisfaction by allocating sufficient frequency and power resources according to traffic demands of the users. In both cases, user groups are selected first to simultaneously transmit their signals at the same frequency resource, while the optimal transmission power level is assigned to each user to optimize the underlying objective function. In addition, the genetic algorithm (GA) approach is employed for user group selection to reduce the computational complexity. When the user traffic rate requirements change rapidly over time, UDB-PF yields better sum rate (throughput) while PUSF provides better network-wide user satisfaction results compared with the PF-based user scheduling. We also observed that the GA-based user group selection significantly reduced the computational load while achieving the comparable results of the exhaustive search.

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Power Allocation for a Downlink Non-Orthogonal Multiple Access System

Cited by 162 publications

References 9 publications

Optimal power allocation for downlink two-user non-orthogonal multiple access in visible light communication

Optimal power allocation for downlink two-user non-orthogonal multiple access in visible light communication

On fair power optimization in nonorthogonal multiple access multiuser networks

User scheduling and power allocation for nonfull buffer traffic in NOMA downlink systems

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