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Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell with Imperfect Hybrid Spectrum Sensing

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Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell with Imperfect Hybrid Spectrum Sensing. / Zhang, Haijun; Nie, Yani; Cheng, Julian; Leung, Victor C.M.; Nallanathan, Arumugam.

In: IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, Vol. 16, No. 2, 01.02.2017, p. 730-743.

Research output: Contribution to journalArticlepeer-review

Harvard

Zhang, H, Nie, Y, Cheng, J, Leung, VCM & Nallanathan, A 2017, 'Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell with Imperfect Hybrid Spectrum Sensing', IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, vol. 16, no. 2, pp. 730-743. https://doi.org/10.1109/TWC.2016.2628821

APA

Zhang, H., Nie, Y., Cheng, J., Leung, V. C. M., & Nallanathan, A. (2017). Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell with Imperfect Hybrid Spectrum Sensing. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 16(2), 730-743. https://doi.org/10.1109/TWC.2016.2628821

Vancouver

Zhang H, Nie Y, Cheng J, Leung VCM, Nallanathan A. Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell with Imperfect Hybrid Spectrum Sensing. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS. 2017 Feb 1;16(2):730-743. https://doi.org/10.1109/TWC.2016.2628821

Author

Zhang, Haijun ; Nie, Yani ; Cheng, Julian ; Leung, Victor C.M. ; Nallanathan, Arumugam. / Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell with Imperfect Hybrid Spectrum Sensing. In: IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS. 2017 ; Vol. 16, No. 2. pp. 730-743.

Bibtex Download

@article{8cedfe4846ab48ff9f01db3b0ca9b4d4,
title = "Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell with Imperfect Hybrid Spectrum Sensing",
abstract = "Cognitive radio enabled small cell network is an emerging technology to address the exponential increase of mobile traffic demand in the next generation mobile communications. Recently, many technological issues such as resource allocation and interference mitigation pertaining to cognitive small cell network have been studied, but most studies focus on maximizing spectral efficiency. Different from the existing works, we investigate the power control and sensing time optimization problem in a cognitive small cell network, where the cross-tier interference mitigation, imperfect hybrid spectrum sensing, and energy efficiency are considered. The optimization of energy efficient sensing time andpower allocation is formulated as a non-convex optimization problem. We solve the proposed problem in an asymptotically optimal manner. An iterative power control algorithm and a near optimal sensing time scheme are developed by considering imperfect hybrid spectrum sensing, cross-tier interferencemitigation, minimum data rate requirement and energy efficiency. Simulation results are presented to verify the effectiveness of the proposed algorithms for energy efficient resource allocation in the cognitive small cell network.",
author = "Haijun Zhang and Yani Nie and Julian Cheng and Leung, {Victor C.M.} and Arumugam Nallanathan",
year = "2017",
month = feb,
day = "1",
doi = "10.1109/TWC.2016.2628821",
language = "English",
volume = "16",
pages = "730--743",
journal = "IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS",
issn = "1536-1276",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "2",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Sensing Time Optimization and Power Control for Energy Efficient Cognitive Small Cell with Imperfect Hybrid Spectrum Sensing

AU - Zhang, Haijun

AU - Nie, Yani

AU - Cheng, Julian

AU - Leung, Victor C.M.

AU - Nallanathan, Arumugam

PY - 2017/2/1

Y1 - 2017/2/1

N2 - Cognitive radio enabled small cell network is an emerging technology to address the exponential increase of mobile traffic demand in the next generation mobile communications. Recently, many technological issues such as resource allocation and interference mitigation pertaining to cognitive small cell network have been studied, but most studies focus on maximizing spectral efficiency. Different from the existing works, we investigate the power control and sensing time optimization problem in a cognitive small cell network, where the cross-tier interference mitigation, imperfect hybrid spectrum sensing, and energy efficiency are considered. The optimization of energy efficient sensing time andpower allocation is formulated as a non-convex optimization problem. We solve the proposed problem in an asymptotically optimal manner. An iterative power control algorithm and a near optimal sensing time scheme are developed by considering imperfect hybrid spectrum sensing, cross-tier interferencemitigation, minimum data rate requirement and energy efficiency. Simulation results are presented to verify the effectiveness of the proposed algorithms for energy efficient resource allocation in the cognitive small cell network.

AB - Cognitive radio enabled small cell network is an emerging technology to address the exponential increase of mobile traffic demand in the next generation mobile communications. Recently, many technological issues such as resource allocation and interference mitigation pertaining to cognitive small cell network have been studied, but most studies focus on maximizing spectral efficiency. Different from the existing works, we investigate the power control and sensing time optimization problem in a cognitive small cell network, where the cross-tier interference mitigation, imperfect hybrid spectrum sensing, and energy efficiency are considered. The optimization of energy efficient sensing time andpower allocation is formulated as a non-convex optimization problem. We solve the proposed problem in an asymptotically optimal manner. An iterative power control algorithm and a near optimal sensing time scheme are developed by considering imperfect hybrid spectrum sensing, cross-tier interferencemitigation, minimum data rate requirement and energy efficiency. Simulation results are presented to verify the effectiveness of the proposed algorithms for energy efficient resource allocation in the cognitive small cell network.

U2 - 10.1109/TWC.2016.2628821

DO - 10.1109/TWC.2016.2628821

M3 - Article

VL - 16

SP - 730

EP - 743

JO - IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS

JF - IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS

SN - 1536-1276

IS - 2

ER -

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