IEICE TRANSACTIONS on Communications
Energy-Efficient and Throughput Maximization Scheme for Sensor-Aided Cognitive Radio Networks
Summary :
A cognitive radio user (CU) can get assistance from sensor nodes (SN) to perform spectrum sensing. However, the SNs are often powered by a finite-capacity battery, which can maintain operations of the SNs over a short time. Therefore, energy-efficiency of the SNs becomes a crucial problem. In this paper, an SN is considered to be a device with an energy harvester that can harvest energy from a non-radio frequency (non-RF) energy resource while performing other actions concurrently. In any one time slot, in order to maintain the required sensing accuracy of the CR network and to conserve energy in the SNs, only a small number of SNs are required to sense the primary user (PU) signal, and other SNs are kept silent to save energy. For this, an algorithm to divide all SNs into groups that can satisfy the required sensing accuracy of the network, is proposed. In a time slot, each SN group can be assigned one of two actions: stay silent, or be active to perform sensing. The problem of determining the optimal action for all SN groups to maximize throughput of the CR network is formulated as a framework of a partially observable Markov decision process (POMDP), in which the effect of the current time slot's action on the throughput of future time slots is considered. The solution to the problem, that is the decision mode of the SN groups (i.e., active or silent), depends on the residual energy and belief of absence probability of the PU signal. The simulation results show that the proposed scheme can improve energy efficiency of CR networks compared with other conventional schemes.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E98-B No.10 pp.1996-2003
- Publication Date
- 2015/10/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E98.B.1996
- Type of Manuscript
- Special Section PAPER (Special Section on 5G Radio Access Networks―Part II: Multi-RAT Heterogeneous Networks and Smart Radio Technologies)
- Category
Authors
Hiep VU-VAN
University of Ulsan
Insoo KOO
University of Ulsan
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Hiep VU-VAN, Insoo KOO, "Energy-Efficient and Throughput Maximization Scheme for Sensor-Aided Cognitive Radio Networks" in IEICE TRANSACTIONS on Communications,
vol. E98-B, no. 10, pp. 1996-2003, October 2015, doi: 10.1587/transcom.E98.B.1996.
Abstract: A cognitive radio user (CU) can get assistance from sensor nodes (SN) to perform spectrum sensing. However, the SNs are often powered by a finite-capacity battery, which can maintain operations of the SNs over a short time. Therefore, energy-efficiency of the SNs becomes a crucial problem. In this paper, an SN is considered to be a device with an energy harvester that can harvest energy from a non-radio frequency (non-RF) energy resource while performing other actions concurrently. In any one time slot, in order to maintain the required sensing accuracy of the CR network and to conserve energy in the SNs, only a small number of SNs are required to sense the primary user (PU) signal, and other SNs are kept silent to save energy. For this, an algorithm to divide all SNs into groups that can satisfy the required sensing accuracy of the network, is proposed. In a time slot, each SN group can be assigned one of two actions: stay silent, or be active to perform sensing. The problem of determining the optimal action for all SN groups to maximize throughput of the CR network is formulated as a framework of a partially observable Markov decision process (POMDP), in which the effect of the current time slot's action on the throughput of future time slots is considered. The solution to the problem, that is the decision mode of the SN groups (i.e., active or silent), depends on the residual energy and belief of absence probability of the PU signal. The simulation results show that the proposed scheme can improve energy efficiency of CR networks compared with other conventional schemes.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E98.B.1996/_p
Copy
@ARTICLE{e98-b_10_1996,
author={Hiep VU-VAN, Insoo KOO, },
journal={IEICE TRANSACTIONS on Communications},
title={Energy-Efficient and Throughput Maximization Scheme for Sensor-Aided Cognitive Radio Networks},
year={2015},
volume={E98-B},
number={10},
pages={1996-2003},
abstract={A cognitive radio user (CU) can get assistance from sensor nodes (SN) to perform spectrum sensing. However, the SNs are often powered by a finite-capacity battery, which can maintain operations of the SNs over a short time. Therefore, energy-efficiency of the SNs becomes a crucial problem. In this paper, an SN is considered to be a device with an energy harvester that can harvest energy from a non-radio frequency (non-RF) energy resource while performing other actions concurrently. In any one time slot, in order to maintain the required sensing accuracy of the CR network and to conserve energy in the SNs, only a small number of SNs are required to sense the primary user (PU) signal, and other SNs are kept silent to save energy. For this, an algorithm to divide all SNs into groups that can satisfy the required sensing accuracy of the network, is proposed. In a time slot, each SN group can be assigned one of two actions: stay silent, or be active to perform sensing. The problem of determining the optimal action for all SN groups to maximize throughput of the CR network is formulated as a framework of a partially observable Markov decision process (POMDP), in which the effect of the current time slot's action on the throughput of future time slots is considered. The solution to the problem, that is the decision mode of the SN groups (i.e., active or silent), depends on the residual energy and belief of absence probability of the PU signal. The simulation results show that the proposed scheme can improve energy efficiency of CR networks compared with other conventional schemes.},
keywords={},
doi={10.1587/transcom.E98.B.1996},
ISSN={1745-1345},
month={October},}
Copy
TY - JOUR
TI - Energy-Efficient and Throughput Maximization Scheme for Sensor-Aided Cognitive Radio Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 1996
EP - 2003
AU - Hiep VU-VAN
AU - Insoo KOO
PY - 2015
DO - 10.1587/transcom.E98.B.1996
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E98-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2015
AB - A cognitive radio user (CU) can get assistance from sensor nodes (SN) to perform spectrum sensing. However, the SNs are often powered by a finite-capacity battery, which can maintain operations of the SNs over a short time. Therefore, energy-efficiency of the SNs becomes a crucial problem. In this paper, an SN is considered to be a device with an energy harvester that can harvest energy from a non-radio frequency (non-RF) energy resource while performing other actions concurrently. In any one time slot, in order to maintain the required sensing accuracy of the CR network and to conserve energy in the SNs, only a small number of SNs are required to sense the primary user (PU) signal, and other SNs are kept silent to save energy. For this, an algorithm to divide all SNs into groups that can satisfy the required sensing accuracy of the network, is proposed. In a time slot, each SN group can be assigned one of two actions: stay silent, or be active to perform sensing. The problem of determining the optimal action for all SN groups to maximize throughput of the CR network is formulated as a framework of a partially observable Markov decision process (POMDP), in which the effect of the current time slot's action on the throughput of future time slots is considered. The solution to the problem, that is the decision mode of the SN groups (i.e., active or silent), depends on the residual energy and belief of absence probability of the PU signal. The simulation results show that the proposed scheme can improve energy efficiency of CR networks compared with other conventional schemes.
ER -
English
