IEICE TRANSACTIONS on Information
Price-Based Power Control Algorithm in Cognitive Radio Networks via Branch and Bound
Summary :
Price-based power control problem is investigated in the spectrum sharing cognitive radio networks (CRNs) by Stackelberg game. Using backward induction, the revenue function of the primary user (PU) is expressed as a non-convex function of the transmit power of the secondary users (SUs). To solve the non-convex problem of the PU, a branch and bound based price-based power control algorithm is proposed. The proposed algorithm can be used to provide performance benchmarks for any other low complexity sub-optimal price-based power control algorithms based on Stackelberg game in CRNs.
- Publication
- IEICE TRANSACTIONS on Information Vol.E102-D No.3 pp.505-511
- Publication Date
- 2019/03/01
- Publicized
- 2018/12/26
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2018EDP7050
- Type of Manuscript
- PAPER
- Category
- Fundamentals of Information Systems
Authors
Zhengqiang WANG
Chongqing University of Posts and Telecommunications
Wenrui XIAO
Chongqing University of Posts and Telecommunications
Xiaoyu WAN
Chongqing University of Posts and Telecommunications
Zifu FAN
Chongqing University of Posts and Telecommunications
Keyword
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Zhengqiang WANG, Wenrui XIAO, Xiaoyu WAN, Zifu FAN, "Price-Based Power Control Algorithm in Cognitive Radio Networks via Branch and Bound" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 3, pp. 505-511, March 2019, doi: 10.1587/transinf.2018EDP7050.
Abstract: Price-based power control problem is investigated in the spectrum sharing cognitive radio networks (CRNs) by Stackelberg game. Using backward induction, the revenue function of the primary user (PU) is expressed as a non-convex function of the transmit power of the secondary users (SUs). To solve the non-convex problem of the PU, a branch and bound based price-based power control algorithm is proposed. The proposed algorithm can be used to provide performance benchmarks for any other low complexity sub-optimal price-based power control algorithms based on Stackelberg game in CRNs.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDP7050/_p
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@ARTICLE{e102-d_3_505,
author={Zhengqiang WANG, Wenrui XIAO, Xiaoyu WAN, Zifu FAN, },
journal={IEICE TRANSACTIONS on Information},
title={Price-Based Power Control Algorithm in Cognitive Radio Networks via Branch and Bound},
year={2019},
volume={E102-D},
number={3},
pages={505-511},
abstract={Price-based power control problem is investigated in the spectrum sharing cognitive radio networks (CRNs) by Stackelberg game. Using backward induction, the revenue function of the primary user (PU) is expressed as a non-convex function of the transmit power of the secondary users (SUs). To solve the non-convex problem of the PU, a branch and bound based price-based power control algorithm is proposed. The proposed algorithm can be used to provide performance benchmarks for any other low complexity sub-optimal price-based power control algorithms based on Stackelberg game in CRNs.},
keywords={},
doi={10.1587/transinf.2018EDP7050},
ISSN={1745-1361},
month={March},}
Copy
TY - JOUR
TI - Price-Based Power Control Algorithm in Cognitive Radio Networks via Branch and Bound
T2 - IEICE TRANSACTIONS on Information
SP - 505
EP - 511
AU - Zhengqiang WANG
AU - Wenrui XIAO
AU - Xiaoyu WAN
AU - Zifu FAN
PY - 2019
DO - 10.1587/transinf.2018EDP7050
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2019
AB - Price-based power control problem is investigated in the spectrum sharing cognitive radio networks (CRNs) by Stackelberg game. Using backward induction, the revenue function of the primary user (PU) is expressed as a non-convex function of the transmit power of the secondary users (SUs). To solve the non-convex problem of the PU, a branch and bound based price-based power control algorithm is proposed. The proposed algorithm can be used to provide performance benchmarks for any other low complexity sub-optimal price-based power control algorithms based on Stackelberg game in CRNs.
ER -
English
