IEICE TRANSACTIONS on Communications
Joint Energy-Efficiency and Throughput Optimization with Admission Control and Resource Allocation in Cognitive Radio Networks
Summary :
In this work, we address a joint energy efficiency (EE) and throughput optimization problem in interweave cognitive radio networks (CRNs) subject to scheduling, power, and stability constraints, which could be solved through traffic admission control, channel allocation, and power allocation. Specifically, the joint objective is to concurrently optimize the system EE and the throughput of secondary user (SU), while satisfying the minimum throughput requirement of primary user (PU), the throughput constraint of SU, and the scheduling and power control constraints that must be considered. To achieve these goals, our algorithm independently and simultaneously makes control decisions on admission and transmission to maximize a joint utility of EE and throughput under time-varying conditions of channel and traffic without a priori knowledge. Specially, the proposed scheduling algorithm has polynomial time efficiency, and the power control algorithms as well as the admission control algorithm involved are simply threshold-based and thus very computationally efficient. Finally, numerical analyses show that our proposals achieve both system stability and optimal utility.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E103-B No.2 pp.139-147
- Publication Date
- 2020/02/01
- Publicized
- 2019/07/26
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2018EBP3182
- Type of Manuscript
- PAPER
- Category
- Terrestrial Wireless Communication/Broadcasting Technologies
Authors
Jain-Shing LIU
Providence University
Chun-Hung LIN
National Sun Yat-sen University
Keyword
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Jain-Shing LIU, Chun-Hung LIN, "Joint Energy-Efficiency and Throughput Optimization with Admission Control and Resource Allocation in Cognitive Radio Networks" in IEICE TRANSACTIONS on Communications,
vol. E103-B, no. 2, pp. 139-147, February 2020, doi: 10.1587/transcom.2018EBP3182.
Abstract: In this work, we address a joint energy efficiency (EE) and throughput optimization problem in interweave cognitive radio networks (CRNs) subject to scheduling, power, and stability constraints, which could be solved through traffic admission control, channel allocation, and power allocation. Specifically, the joint objective is to concurrently optimize the system EE and the throughput of secondary user (SU), while satisfying the minimum throughput requirement of primary user (PU), the throughput constraint of SU, and the scheduling and power control constraints that must be considered. To achieve these goals, our algorithm independently and simultaneously makes control decisions on admission and transmission to maximize a joint utility of EE and throughput under time-varying conditions of channel and traffic without a priori knowledge. Specially, the proposed scheduling algorithm has polynomial time efficiency, and the power control algorithms as well as the admission control algorithm involved are simply threshold-based and thus very computationally efficient. Finally, numerical analyses show that our proposals achieve both system stability and optimal utility.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018EBP3182/_p
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@ARTICLE{e103-b_2_139,
author={Jain-Shing LIU, Chun-Hung LIN, },
journal={IEICE TRANSACTIONS on Communications},
title={Joint Energy-Efficiency and Throughput Optimization with Admission Control and Resource Allocation in Cognitive Radio Networks},
year={2020},
volume={E103-B},
number={2},
pages={139-147},
abstract={In this work, we address a joint energy efficiency (EE) and throughput optimization problem in interweave cognitive radio networks (CRNs) subject to scheduling, power, and stability constraints, which could be solved through traffic admission control, channel allocation, and power allocation. Specifically, the joint objective is to concurrently optimize the system EE and the throughput of secondary user (SU), while satisfying the minimum throughput requirement of primary user (PU), the throughput constraint of SU, and the scheduling and power control constraints that must be considered. To achieve these goals, our algorithm independently and simultaneously makes control decisions on admission and transmission to maximize a joint utility of EE and throughput under time-varying conditions of channel and traffic without a priori knowledge. Specially, the proposed scheduling algorithm has polynomial time efficiency, and the power control algorithms as well as the admission control algorithm involved are simply threshold-based and thus very computationally efficient. Finally, numerical analyses show that our proposals achieve both system stability and optimal utility.},
keywords={},
doi={10.1587/transcom.2018EBP3182},
ISSN={1745-1345},
month={February},}
Copy
TY - JOUR
TI - Joint Energy-Efficiency and Throughput Optimization with Admission Control and Resource Allocation in Cognitive Radio Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 139
EP - 147
AU - Jain-Shing LIU
AU - Chun-Hung LIN
PY - 2020
DO - 10.1587/transcom.2018EBP3182
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E103-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2020
AB - In this work, we address a joint energy efficiency (EE) and throughput optimization problem in interweave cognitive radio networks (CRNs) subject to scheduling, power, and stability constraints, which could be solved through traffic admission control, channel allocation, and power allocation. Specifically, the joint objective is to concurrently optimize the system EE and the throughput of secondary user (SU), while satisfying the minimum throughput requirement of primary user (PU), the throughput constraint of SU, and the scheduling and power control constraints that must be considered. To achieve these goals, our algorithm independently and simultaneously makes control decisions on admission and transmission to maximize a joint utility of EE and throughput under time-varying conditions of channel and traffic without a priori knowledge. Specially, the proposed scheduling algorithm has polynomial time efficiency, and the power control algorithms as well as the admission control algorithm involved are simply threshold-based and thus very computationally efficient. Finally, numerical analyses show that our proposals achieve both system stability and optimal utility.
ER -
English
