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Maximizing energy efficiency in multiuser multicarrier broadband wireless systems: convex relaxation and global optimization techniques

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Maximizing energy efficiency in multiuser multicarrier broadband wireless systems : convex relaxation and global optimization techniques. / Zarakovitis, Charilaos C.; Ni, Qiang.

In: IEEE Transactions on Vehicular Technology, Vol. 65, No. 7, 07.2016, p. 5275-5286.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Zarakovitis CC, Ni Q. Maximizing energy efficiency in multiuser multicarrier broadband wireless systems: convex relaxation and global optimization techniques. IEEE Transactions on Vehicular Technology. 2016 Jul;65(7):5275-5286. Epub 2015 Jul 13. doi: 10.1109/TVT.2015.2455536

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@article{8bb4b250d7474888a3909869a683e924,
title = "Maximizing energy efficiency in multiuser multicarrier broadband wireless systems: convex relaxation and global optimization techniques",
abstract = "A key challenge toward green communications is how to maximize energy efficiency by optimally allocating wireless resources in large-scale multiuser multicarrier orthogonal frequency-division multiple-access (OFDMA) systems. The quality-of-service (QoS)-constrained energy efficiency maximization problem is generally hard to solve due to the inverse transposition of the optimization operands in the optimization objective. We apply convex relaxation to make the problem quasiconcave with respect to power and concave with respect to the subcarrier indexing coefficients. The Karush-Kuhn-Tucker (KKT) optimality conditions lead to transcendental functions, where existing solutions are only numerically tractable. Different from the existing approaches, we apply the Maclaurin series expansion technique to transform the complex transcendental functions into simple polynomial expressions that allow us to obtain the global optimum in fast polynomial time, with the tractable upper bound of truncation error. With the new solution method, we propose a joint optimal allocation policy for both adaptive power and dynamic subcarrier allocations. We gain insight on the optimality, feasibility, and computational complexity of the joint optimal solution to show that the proposed scheme is theoretically and practically sound with fast convergence toward near-optimal solutions with an explicitly tractable truncation error. The simulation results confirm that the proposed scheme achieves a much higher energy efficiency performance with the guaranteed QoS and much lower complexity than existing approaches in the literature.",
author = "Zarakovitis, {Charilaos C.} and Qiang Ni",
year = "2016",
month = jul,
doi = "10.1109/TVT.2015.2455536",
language = "English",
volume = "65",
pages = "5275--5286",
journal = "IEEE Transactions on Vehicular Technology",
issn = "0018-9545",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "7",

}

RIS

TY - JOUR

T1 - Maximizing energy efficiency in multiuser multicarrier broadband wireless systems

T2 - convex relaxation and global optimization techniques

AU - Zarakovitis, Charilaos C.

AU - Ni, Qiang

PY - 2016/7

Y1 - 2016/7

N2 - A key challenge toward green communications is how to maximize energy efficiency by optimally allocating wireless resources in large-scale multiuser multicarrier orthogonal frequency-division multiple-access (OFDMA) systems. The quality-of-service (QoS)-constrained energy efficiency maximization problem is generally hard to solve due to the inverse transposition of the optimization operands in the optimization objective. We apply convex relaxation to make the problem quasiconcave with respect to power and concave with respect to the subcarrier indexing coefficients. The Karush-Kuhn-Tucker (KKT) optimality conditions lead to transcendental functions, where existing solutions are only numerically tractable. Different from the existing approaches, we apply the Maclaurin series expansion technique to transform the complex transcendental functions into simple polynomial expressions that allow us to obtain the global optimum in fast polynomial time, with the tractable upper bound of truncation error. With the new solution method, we propose a joint optimal allocation policy for both adaptive power and dynamic subcarrier allocations. We gain insight on the optimality, feasibility, and computational complexity of the joint optimal solution to show that the proposed scheme is theoretically and practically sound with fast convergence toward near-optimal solutions with an explicitly tractable truncation error. The simulation results confirm that the proposed scheme achieves a much higher energy efficiency performance with the guaranteed QoS and much lower complexity than existing approaches in the literature.

AB - A key challenge toward green communications is how to maximize energy efficiency by optimally allocating wireless resources in large-scale multiuser multicarrier orthogonal frequency-division multiple-access (OFDMA) systems. The quality-of-service (QoS)-constrained energy efficiency maximization problem is generally hard to solve due to the inverse transposition of the optimization operands in the optimization objective. We apply convex relaxation to make the problem quasiconcave with respect to power and concave with respect to the subcarrier indexing coefficients. The Karush-Kuhn-Tucker (KKT) optimality conditions lead to transcendental functions, where existing solutions are only numerically tractable. Different from the existing approaches, we apply the Maclaurin series expansion technique to transform the complex transcendental functions into simple polynomial expressions that allow us to obtain the global optimum in fast polynomial time, with the tractable upper bound of truncation error. With the new solution method, we propose a joint optimal allocation policy for both adaptive power and dynamic subcarrier allocations. We gain insight on the optimality, feasibility, and computational complexity of the joint optimal solution to show that the proposed scheme is theoretically and practically sound with fast convergence toward near-optimal solutions with an explicitly tractable truncation error. The simulation results confirm that the proposed scheme achieves a much higher energy efficiency performance with the guaranteed QoS and much lower complexity than existing approaches in the literature.

U2 - 10.1109/TVT.2015.2455536

DO - 10.1109/TVT.2015.2455536

M3 - Journal article

VL - 65

SP - 5275

EP - 5286

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

SN - 0018-9545

IS - 7

ER -