Convex Approximated Weighted Sum-Rate Maximization for Multicell Multiuser OFDM
Summary :
This letter considers the weighted sum-rate maximization (WSRMax) problem in downlink multicell multiuser orthogonal frequency-division multiplexing system. The WSRMax problem under per base station transmit power constraint is known to be NP-hard, and the optimal solution is computationally very expensive. We propose two less-complex suboptimal convex approximated solutions which are based on sequential parametric convex approximation approach. We derive provably faster convergent iterative convex approximation techniques that locally optimize the weighted sum-rate function. Both the iterative solutions are found to converge to the local optimal solution within a few iterations compared to other well-known techniques. The numerical results demonstrate the effectiveness and superiority of the proposed approaches.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E97-A No.8 pp.1800-1805
- Publication Date
- 2014/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E97.A.1800
- Type of Manuscript
- LETTER
- Category
- Numerical Analysis and Optimization
Authors
Mirza Golam KIBRIA
Kyoto University
Hidekazu MURATA
Kyoto University
Keyword
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Mirza Golam KIBRIA, Hidekazu MURATA, "Convex Approximated Weighted Sum-Rate Maximization for Multicell Multiuser OFDM" in IEICE TRANSACTIONS on Fundamentals,
vol. E97-A, no. 8, pp. 1800-1805, August 2014, doi: 10.1587/transfun.E97.A.1800.
Abstract: This letter considers the weighted sum-rate maximization (WSRMax) problem in downlink multicell multiuser orthogonal frequency-division multiplexing system. The WSRMax problem under per base station transmit power constraint is known to be NP-hard, and the optimal solution is computationally very expensive. We propose two less-complex suboptimal convex approximated solutions which are based on sequential parametric convex approximation approach. We derive provably faster convergent iterative convex approximation techniques that locally optimize the weighted sum-rate function. Both the iterative solutions are found to converge to the local optimal solution within a few iterations compared to other well-known techniques. The numerical results demonstrate the effectiveness and superiority of the proposed approaches.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E97.A.1800/_p
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@ARTICLE{e97-a_8_1800,
author={Mirza Golam KIBRIA, Hidekazu MURATA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Convex Approximated Weighted Sum-Rate Maximization for Multicell Multiuser OFDM},
year={2014},
volume={E97-A},
number={8},
pages={1800-1805},
abstract={This letter considers the weighted sum-rate maximization (WSRMax) problem in downlink multicell multiuser orthogonal frequency-division multiplexing system. The WSRMax problem under per base station transmit power constraint is known to be NP-hard, and the optimal solution is computationally very expensive. We propose two less-complex suboptimal convex approximated solutions which are based on sequential parametric convex approximation approach. We derive provably faster convergent iterative convex approximation techniques that locally optimize the weighted sum-rate function. Both the iterative solutions are found to converge to the local optimal solution within a few iterations compared to other well-known techniques. The numerical results demonstrate the effectiveness and superiority of the proposed approaches.},
keywords={},
doi={10.1587/transfun.E97.A.1800},
ISSN={1745-1337},
month={August},}
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TY - JOUR
TI - Convex Approximated Weighted Sum-Rate Maximization for Multicell Multiuser OFDM
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1800
EP - 1805
AU - Mirza Golam KIBRIA
AU - Hidekazu MURATA
PY - 2014
DO - 10.1587/transfun.E97.A.1800
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E97-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2014
AB - This letter considers the weighted sum-rate maximization (WSRMax) problem in downlink multicell multiuser orthogonal frequency-division multiplexing system. The WSRMax problem under per base station transmit power constraint is known to be NP-hard, and the optimal solution is computationally very expensive. We propose two less-complex suboptimal convex approximated solutions which are based on sequential parametric convex approximation approach. We derive provably faster convergent iterative convex approximation techniques that locally optimize the weighted sum-rate function. Both the iterative solutions are found to converge to the local optimal solution within a few iterations compared to other well-known techniques. The numerical results demonstrate the effectiveness and superiority of the proposed approaches.
ER -
English
