Cognitive orthogonal frequency-division multiplexing (OFDM) systems are spectrum-efficient yet vulnerable to intercarrier interference (ICI), especially in high-mobility scenarios. In this paper, the energy efficiency optimization problem in high-mobility cognitive OFDM system is considered. The aim is to maximize the energy efficiency by adapting subcarrier bandwidth, power allocation and sensing duration in the presence of ICI, under the constraints of the total power budget of secondary networks, the probabilistic interference limits for the protection of primary networks, and the subcarrier spacing restriction for high-mobility OFDM systems. In order to tackle the intractable non-convex optimization problem induced by ICI, an ICI-aware power allocation algorithm is proposed, by referring to noncooperative game theory. Moreover, a near-optimal subcarrier bandwidth search algorithm based on golden section methods is also presented to maximize the system energy efficiency. Simulation results show that the proposed algorithms can achieve a considerable energy efficiency improvement by up to 133% compared to the traditional static subcarrier bandwidth and power allocation schemes.
Wenjun XU
Beijing University of Posts and Telecommunications
Xuemei ZHOU
Beijing University of Posts and Telecommunications
Yanda CHEN
Beijing University of Posts and Telecommunications
Zhihui LIU
Beijing University of Posts and Telecommunications
Zhiyong FENG
Beijing University of Posts and Telecommunications
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Wenjun XU, Xuemei ZHOU, Yanda CHEN, Zhihui LIU, Zhiyong FENG, "Intercarrier-Interference-Aware Energy Saving for High-Mobility Cognitive OFDM Systems" in IEICE TRANSACTIONS on Communications,
vol. E101-B, no. 1, pp. 203-212, January 2018, doi: 10.1587/transcom.2017EBP3096.
Abstract: Cognitive orthogonal frequency-division multiplexing (OFDM) systems are spectrum-efficient yet vulnerable to intercarrier interference (ICI), especially in high-mobility scenarios. In this paper, the energy efficiency optimization problem in high-mobility cognitive OFDM system is considered. The aim is to maximize the energy efficiency by adapting subcarrier bandwidth, power allocation and sensing duration in the presence of ICI, under the constraints of the total power budget of secondary networks, the probabilistic interference limits for the protection of primary networks, and the subcarrier spacing restriction for high-mobility OFDM systems. In order to tackle the intractable non-convex optimization problem induced by ICI, an ICI-aware power allocation algorithm is proposed, by referring to noncooperative game theory. Moreover, a near-optimal subcarrier bandwidth search algorithm based on golden section methods is also presented to maximize the system energy efficiency. Simulation results show that the proposed algorithms can achieve a considerable energy efficiency improvement by up to 133% compared to the traditional static subcarrier bandwidth and power allocation schemes.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.2017EBP3096/_p
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@ARTICLE{e101-b_1_203,
author={Wenjun XU, Xuemei ZHOU, Yanda CHEN, Zhihui LIU, Zhiyong FENG, },
journal={IEICE TRANSACTIONS on Communications},
title={Intercarrier-Interference-Aware Energy Saving for High-Mobility Cognitive OFDM Systems},
year={2018},
volume={E101-B},
number={1},
pages={203-212},
abstract={Cognitive orthogonal frequency-division multiplexing (OFDM) systems are spectrum-efficient yet vulnerable to intercarrier interference (ICI), especially in high-mobility scenarios. In this paper, the energy efficiency optimization problem in high-mobility cognitive OFDM system is considered. The aim is to maximize the energy efficiency by adapting subcarrier bandwidth, power allocation and sensing duration in the presence of ICI, under the constraints of the total power budget of secondary networks, the probabilistic interference limits for the protection of primary networks, and the subcarrier spacing restriction for high-mobility OFDM systems. In order to tackle the intractable non-convex optimization problem induced by ICI, an ICI-aware power allocation algorithm is proposed, by referring to noncooperative game theory. Moreover, a near-optimal subcarrier bandwidth search algorithm based on golden section methods is also presented to maximize the system energy efficiency. Simulation results show that the proposed algorithms can achieve a considerable energy efficiency improvement by up to 133% compared to the traditional static subcarrier bandwidth and power allocation schemes.},
keywords={},
doi={10.1587/transcom.2017EBP3096},
ISSN={1745-1345},
month={January},}
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TY - JOUR
TI - Intercarrier-Interference-Aware Energy Saving for High-Mobility Cognitive OFDM Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 203
EP - 212
AU - Wenjun XU
AU - Xuemei ZHOU
AU - Yanda CHEN
AU - Zhihui LIU
AU - Zhiyong FENG
PY - 2018
DO - 10.1587/transcom.2017EBP3096
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E101-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2018
AB - Cognitive orthogonal frequency-division multiplexing (OFDM) systems are spectrum-efficient yet vulnerable to intercarrier interference (ICI), especially in high-mobility scenarios. In this paper, the energy efficiency optimization problem in high-mobility cognitive OFDM system is considered. The aim is to maximize the energy efficiency by adapting subcarrier bandwidth, power allocation and sensing duration in the presence of ICI, under the constraints of the total power budget of secondary networks, the probabilistic interference limits for the protection of primary networks, and the subcarrier spacing restriction for high-mobility OFDM systems. In order to tackle the intractable non-convex optimization problem induced by ICI, an ICI-aware power allocation algorithm is proposed, by referring to noncooperative game theory. Moreover, a near-optimal subcarrier bandwidth search algorithm based on golden section methods is also presented to maximize the system energy efficiency. Simulation results show that the proposed algorithms can achieve a considerable energy efficiency improvement by up to 133% compared to the traditional static subcarrier bandwidth and power allocation schemes.
ER -