Price-Based Power Allocation with Rate Proportional Fairness Constraint in Downlink Non-Orthogonal Multiple Access Systems

Fan, Zifu; Wen, Chen-chen; Wang, Zhengqiang; Wang, Xiaoyu

doi:10.1587/transfun.e100.a.2543

Cited by 3 publications

(18 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed algorithm is compared with exhaustive search result and algorithms in to evaluate and compare the performance. The number of users that should be scheduled, M , is considered as 5 for the simulations, and channel gains

h_{m}

are modeled as Gaussian random variables with variances corresponding to 0.2, 0.4, 0.6, 0.8, and 1 for the first to the fifth user, respectively, unless otherwise specified.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The proposed algorithm converges to the optimal solution obtained via an exhaustive search at all SNRs as shown in the figures. The values exceed those in . This is because correspond to suboptimal algorithms, and the rate constraint in degrades the total revenue of the BS.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…A fast algorithm is also proposed to solve the set of equations iteratively based on the univariate bisection method. The proposed algorithm outperforms the schemes in terms of revenue of the BS and sum rate of users, and it converges to the optimal solution. To the best of the author's knowledge, there is a paucity of a comprehensive study of price‐based NOMA systems. The problem of optimal user selection is not addressed in .…”

Section: Introductionmentioning

confidence: 90%

“…The proposed algorithm outperforms the schemes in terms of revenue of the BS and sum rate of users, and it converges to the optimal solution. To the best of the author's knowledge, there is a paucity of a comprehensive study of price‐based NOMA systems. The problem of optimal user selection is not addressed in . Thus, in addition to optimal power allocation algorithm, we propose an efficient method for user selection. A novel and simple albeit efficient low complexity algorithm for combined user selection and power allocation is presented in this study. We investigate the effect of the optimal solution on the sum rate and user fairness.…”

Section: Introductionmentioning

confidence: 90%

“…Based on the model, the revenue‐based power allocation problem is formulated as a Stackelberg game where BS denotes the leader and M users correspond to the followers . The leader charges the m th user a price of

λ_{m}

per unit allocated power.…”

Section: System Modelmentioning

confidence: 99%

See 4 more Smart Citations

Optimal user selection and power allocation for revenue maximization in non‐orthogonal multiple access systems

Pazhayakandathil

Sukumaran

Koodamannu³

2019

ETRI Journal

View full text Add to dashboard Cite

A novel algorithm for joint user selection and optimal power allocation for Stackelberg game‐based revenue maximization in a downlink non‐orthogonal multiple access (NOMA) network is proposed in this study. The condition for the existence of optimal solution is derived by assuming perfect channel state information (CSI) at the transmitter. The Lagrange multiplier method is used to convert the revenue maximization problem into a set of quadratic equations that are reduced to a regular chain of expressions. The optimal solution is obtained via a univariate iterative procedure. A simple algorithm for joint optimal user selection and power calculation is presented and exhibits extremely low complexity. Furthermore, an outage analysis is presented to evaluate the performance degradation when perfect CSI is not available. The simulation results indicate that at 5‐dB signal‐to‐noise ratio (SNR), revenue of the base station improves by at least 15.2% for the proposed algorithm when compared to suboptimal schemes. Other performance metrics of NOMA, such as individual user‐rates, fairness index, and outage probability, approach near‐optimal values at moderate to high SNRs.

show abstract

h_{m}

are modeled as Gaussian random variables with variances corresponding to 0.2, 0.4, 0.6, 0.8, and 1 for the first to the fifth user, respectively, unless otherwise specified.…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 90%

λ_{m}

per unit allocated power.…”

Section: System Modelmentioning

confidence: 99%

See 3 more Smart Citations

Optimal user selection and power allocation for revenue maximization in non‐orthogonal multiple access systems

Pazhayakandathil

Sukumaran

Koodamannu³

2019

ETRI Journal

View full text Add to dashboard Cite

show abstract

NOMA and 5G emerging technologies: A survey on issues and solution techniques

2021

View full text Add to dashboard Cite

A Fairness Index Based on Rate Variance for Downlink Non-Orthogonal Multiple Access System

2022

View full text Add to dashboard Cite

Aiming at the resource allocation problem of a non-orthogonal multiple access (NOMA) system, a fairness index based on sample variance of users’ transmission rates is proposed, which has a fixed range and high sensitivity. Based on the proposed fairness index, the fairness-constrained power allocation problem in NOMA system is studied; the problem is decoupled into the intra cluster power allocation problem and the inter cluster power allocation problem. The nonconvex optimization problem is solved by the continuous convex approximation (SCA) method, and an intra and inter cluster power iterative allocation algorithm with fairness constrained is proposed to maximize the total throughput. Simulation results show that the proposed algorithm can take into account intra cluster, inter cluster, and system fairness, and maximize the system throughput on the premise of fairness.

show abstract

Price-Based Power Allocation with Rate Proportional Fairness Constraint in Downlink Non-Orthogonal Multiple Access Systems

Cited by 3 publications

References 10 publications

Optimal user selection and power allocation for revenue maximization in non‐orthogonal multiple access systems

Optimal user selection and power allocation for revenue maximization in non‐orthogonal multiple access systems

NOMA and 5G emerging technologies: A survey on issues and solution techniques

A Fairness Index Based on Rate Variance for Downlink Non-Orthogonal Multiple Access System

Contact Info

Product

Resources

About