Energy-Efficient Subcarrier Assignment and Power Allocation in OFDMA Systems With Max-Min Fairness Guarantees

Li, Yuzhou; Sheng, Min; Tan, Chee Wei; Zhang, Yan; Sun, Yuhua; Wang, Xijun; Shi, Yan; Li, Jiandong

doi:10.1109/tcomm.2015.2450724

Cited by 106 publications

(74 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on the Theorem 2, we have the following Propositions for the problem (27). Based on the Theorem 2, we have the following Propositions for the problem (27).…”

Section: Max-min Energy Efficiencymentioning

confidence: 99%

See 1 more Smart Citation

Energy‐efficient power control for uplink spectrum‐sharing heterogeneous networks

Pham

Hwang

2018

Int J Communication

View full text Add to dashboard Cite

This article considers energy-efficient power control schemes for interference management in uplink spectrum-sharing heterogeneous networks that maximize the energy efficiency of users, protect the macro base station, and support users with QoS consideration. In the first scenario, we define the objective function as the weighted sum of the energy efficiencies and develop an efficient global optimization algorithm with global linear and local quadratic rate of convergence to solve the considered problem. To ensure fairness among individual user equipments (UEs) in terms of energy efficiency, we consider the max-min problem, where the objective is defined as the weighted minimum of the energy efficiencies, and a fractional programming theory and the dual decomposition method are jointly used to solve the problem and investigate an iterative algorithm. As by-products, we further discuss the global energy efficiency problem and consider near-optimal schemes. Numerical examples are provided to demonstrate significant improvements of the proposed algorithms over existing interference management schemes. KEYWORDS energy efficiency, heterogeneous networks, interference management, power control, sum-of-ratios Quoc-Viet Pham was with

show abstract

“…Based on the Theorem 2, we have the following Propositions for the problem (27). Based on the Theorem 2, we have the following Propositions for the problem (27).…”

Section: Max-min Energy Efficiencymentioning

confidence: 99%

“…Consequently, (27) is a jointly convex problem that maximizes a concave objective function over a convex set. According to Proposition 1, the first, second, and third constraint are all convex.…”

Section: Proposition 2 For Given and Problem (27) Is A Jointly Conmentioning

confidence: 99%

Energy‐efficient power control for uplink spectrum‐sharing heterogeneous networks

Pham

Hwang

2018

Int J Communication

View full text Add to dashboard Cite

show abstract

“…One of the most commonly used definitions for EE in the available literature is the data rate to the power consumption ratio . The EE of u ( k ) on the n th subchannel is defined as follows:

η_{k, u}^{EE} ((), p, a) = \frac{R_{k, u}^{F} ((), p, a)}{{pc}_{k, u}^{F} ((), p, a)}, \forall k \in scriptK, \forall u \in U_{k},

where

{pc}_{k, u}^{F} ((), p, a) = ξ_{k, u} p_{k, u} ((), p, a) + p_{k, u}^{c}

denotes the power consumption of u ( k ).…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…As a remark, the final results of the work of Li et al can be improved significantly just by implementing the idea at subchannel assignment.…”

Section: Proposed Subchannel Assignment For Scusmentioning

confidence: 99%

Max‐min energy‐efficient subchannel assignment and power allocation in interference‐limited OFDMA heterogeneous networks with QoS guarantee

Mohammadian

Dehghani

Eslami

et al. 2018

Trans Emerging Tel Tech

View full text Add to dashboard Cite

This paper investigates fairness among all small‐cell users (SCUs) in terms of energy efficiency for the uplink transmission of interference‐limited orthogonal frequency‐division multiple access–based heterogeneous networks. Each SCU is treated by a minimum data rate. In addition, a maximum tolerable interference for the macro base station has been considered. The resulting resource allocation problem is formulated as a nonconvex mixed‐integer nonlinear problem. In order to solve the mixed‐integer nonlinear problem, the subchannel assignment and the power allocation are applied separately; an efficient subchannel assignment algorithm has been proposed where the co‐tier and cross‐tier interference in the most general form has been taken into account. Then, to solve the power allocation subproblem, an iterative algorithm has been proposed by applying generalized fractional programming and sequential convex programming when a specified subchannel assignment is in hand. Performance of the proposed model has been evaluated, and simulation results indicate a fair resource allocation with a very high energy efficiency among SCUs comparing the state‐of‐the‐art solutions.

show abstract

“…[1][2][3][4][5] Del Castillo et al 6 analyzed the OFDMA resource allocation problem in broadband wireless using IEEE 802. Because of orthogonality between subcarriers and by exploiting multiuser (MU) diversity along with adaptive resource allocation, OFDMA provides improved system performance.…”

Section: Introductionmentioning

confidence: 99%

Hungarian algorithm for subcarrier assignment problem using GPU and CUDA

Yadav

Lopes

Ilić

et al. 2018

Int J Communication

View full text Add to dashboard Cite

General purpose graphics processing units (GPGPUs) have gained much popularity in scientific computing to speedup computational intensive workloads.Resource allocation in terms of power and subcarriers assignment, in current wireless standards, is one of the challenging problems due to its high computational complexity requirement. The Hungarian algorithm (HA), which has been extensively applied to linear assignment problems (LAPs), has been seen to provide encouraging result in resource allocation for wireless communication systems. This paper presents a compute unified device architecture (CUDA) implementation of the HA on graphics processing unit (GPU) for this problem.HA has been implemented on a parallel architecture to solve the subcarrier assignment problem and maximize spectral efficiency. The proposed implementation is achieved by using the "Kuhn-Munkres" algorithm with effective modifications, in order to fully exploit the capabilities of modern GPU devices. A cost matrix for maximum assignment has been defined leading to a low complexity matrix compression along with highly optimized CUDA reduction and parallel alternating path search process. All these optimizations lead to an efficient implementation with superior performance when compared with existing parallel implementations. KEYWORDSCUDA, GPU, OFDMA, parallel Hungarian algorithm, subcarrier assignment Int J Commun Syst. 2019;32:e3884.wileyonlinelibrary.com/journal/dac

show abstract

Energy-Efficient Subcarrier Assignment and Power Allocation in OFDMA Systems With Max-Min Fairness Guarantees

Cited by 106 publications

References 37 publications

Energy‐efficient power control for uplink spectrum‐sharing heterogeneous networks

Energy‐efficient power control for uplink spectrum‐sharing heterogeneous networks

Max‐min energy‐efficient subchannel assignment and power allocation in interference‐limited OFDMA heterogeneous networks with QoS guarantee

Hungarian algorithm for subcarrier assignment problem using GPU and CUDA

Contact Info

Product

Resources

About