Simple Weighted Diversity Combining Technique for Cyclostationarity Detection Based Spectrum Sensing in Cognitive Radio Networks

Daiki CHO; Shusuke NARIEDA

doi:10.1587/transcom.2015EBP3524

Simple Weighted Diversity Combining Technique for Cyclostationarity Detection Based Spectrum Sensing in Cognitive Radio Networks

Daiki CHO, Shusuke NARIEDA

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This paper presents a weighted diversity combining technique for the cyclostationarity detection based spectrum sensing of orthogonal frequency division multiplexing signals in cognitive radio. In cognitive radio systems, secondary users must detect the desired signal in an extremely low signal-to-noise ratio (SNR) environment. In such an environment, multiple antenna techniques (space diversity) such as maximum ratio combining are not effective because the energy of the target signal is also extremely weak, and it is difficult to synchronize some received signals. The cyclic autocorrelation function (CAF) is used for traditional cyclostationarity detection based spectrum sensing. In the presented technique, the CAFs of the received signals are combined, while the received signals themselves are combined with general space diversity techniques. In this paper, the value of the CAF at peak and non-peak cyclic frequencies are computed, and we attempt to improve the sensing performance by using different weights for each CAF value. The results were compared with those from conventional methods and showed that the presented technique can improve the spectrum sensing performance.

Publication: IEICE TRANSACTIONS on Communications Vol.E99-B No.10 pp.2212-2220

Publication Date: 2016/10/01

Publicized: 2016/04/08

Online ISSN: 1745-1345

DOI: 10.1587/transcom.2015EBP3524

Type of Manuscript: PAPER

Category: Wireless Communication Technologies

Authors

Daiki CHO
Akashi College
Shusuke NARIEDA
Akashi College

Keyword

cognitive radio network, cyclostationarity detection based spectrum sensing, space diversity, orthogonal frequency division multiplexing signal

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Daiki CHO, Shusuke NARIEDA, "Simple Weighted Diversity Combining Technique for Cyclostationarity Detection Based Spectrum Sensing in Cognitive Radio Networks" in IEICE TRANSACTIONS on Communications, vol. E99-B, no. 10, pp. 2212-2220, October 2016, doi: 10.1587/transcom.2015EBP3524.
Abstract: This paper presents a weighted diversity combining technique for the cyclostationarity detection based spectrum sensing of orthogonal frequency division multiplexing signals in cognitive radio. In cognitive radio systems, secondary users must detect the desired signal in an extremely low signal-to-noise ratio (SNR) environment. In such an environment, multiple antenna techniques (space diversity) such as maximum ratio combining are not effective because the energy of the target signal is also extremely weak, and it is difficult to synchronize some received signals. The cyclic autocorrelation function (CAF) is used for traditional cyclostationarity detection based spectrum sensing. In the presented technique, the CAFs of the received signals are combined, while the received signals themselves are combined with general space diversity techniques. In this paper, the value of the CAF at peak and non-peak cyclic frequencies are computed, and we attempt to improve the sensing performance by using different weights for each CAF value. The results were compared with those from conventional methods and showed that the presented technique can improve the spectrum sensing performance.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.2015EBP3524/_p

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@ARTICLE{e99-b_10_2212,
author={Daiki CHO, Shusuke NARIEDA, },
journal={IEICE TRANSACTIONS on Communications},
title={Simple Weighted Diversity Combining Technique for Cyclostationarity Detection Based Spectrum Sensing in Cognitive Radio Networks},
year={2016},
volume={E99-B},
number={10},
pages={2212-2220},
abstract={This paper presents a weighted diversity combining technique for the cyclostationarity detection based spectrum sensing of orthogonal frequency division multiplexing signals in cognitive radio. In cognitive radio systems, secondary users must detect the desired signal in an extremely low signal-to-noise ratio (SNR) environment. In such an environment, multiple antenna techniques (space diversity) such as maximum ratio combining are not effective because the energy of the target signal is also extremely weak, and it is difficult to synchronize some received signals. The cyclic autocorrelation function (CAF) is used for traditional cyclostationarity detection based spectrum sensing. In the presented technique, the CAFs of the received signals are combined, while the received signals themselves are combined with general space diversity techniques. In this paper, the value of the CAF at peak and non-peak cyclic frequencies are computed, and we attempt to improve the sensing performance by using different weights for each CAF value. The results were compared with those from conventional methods and showed that the presented technique can improve the spectrum sensing performance.},
keywords={},
doi={10.1587/transcom.2015EBP3524},
ISSN={1745-1345},
month={October},}

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TY - JOUR
TI - Simple Weighted Diversity Combining Technique for Cyclostationarity Detection Based Spectrum Sensing in Cognitive Radio Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 2212
EP - 2220
AU - Daiki CHO
AU - Shusuke NARIEDA
PY - 2016
DO - 10.1587/transcom.2015EBP3524
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2016
AB - This paper presents a weighted diversity combining technique for the cyclostationarity detection based spectrum sensing of orthogonal frequency division multiplexing signals in cognitive radio. In cognitive radio systems, secondary users must detect the desired signal in an extremely low signal-to-noise ratio (SNR) environment. In such an environment, multiple antenna techniques (space diversity) such as maximum ratio combining are not effective because the energy of the target signal is also extremely weak, and it is difficult to synchronize some received signals. The cyclic autocorrelation function (CAF) is used for traditional cyclostationarity detection based spectrum sensing. In the presented technique, the CAFs of the received signals are combined, while the received signals themselves are combined with general space diversity techniques. In this paper, the value of the CAF at peak and non-peak cyclic frequencies are computed, and we attempt to improve the sensing performance by using different weights for each CAF value. The results were compared with those from conventional methods and showed that the presented technique can improve the spectrum sensing performance.
ER -