IEICE TRANSACTIONS on Communications
Robust and Low Complexity Bandwidth and Carrier Frequency Estimation for Cognitive Radio
Summary :
Cognitive radio (CR) is an important technology to provide high-efficiency data communication for the IoT (Internet of Things) era. Signal detection is a key technology of CR to detect communication opportunities. Energy detection (ED) is a signal detection method that does not have high computational complexity. It, however, can only estimate the presence or absence of signal(s) in the observed band. Cyclostationarity detection (CS) is an alternative signal detection method. This method detects some signal features like periodicity. It can estimate the symbol rate of a signal if present. It, however, incurs high computational complexity. In addition, it cannot estimate the symbol rate precisely in the case of single carrier signal with a low Roll-Off factor (ROF). This paper proposes a method to estimate coarsely a signal's bandwidth and carrier frequency from its power spectrum with lower computational complexity than the CS. The proposed method can estimate the bandwidth and carrier frequency of even a low ROF signal. This paper evaluates the proposed method's performance by numerical simulations. The numerical results show that in all cases the proposed coarse bandwidth and carrier frequency estimation is almost comparable to the performance of CS with lower computational complexity and even outperforms in the case of single carrier signal with a low ROF. The proposed method is generally effective for unidentified classification of the signal i.e. single carrier, OFDM etc.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E99-B No.2 pp.499-506
- Publication Date
- 2016/02/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2015EBP3265
- Type of Manuscript
- PAPER
- Category
- Wireless Communication Technologies
Authors
Hiroyuki KAMATA
Tokyo Institute of Technology
Gia Khanh TRAN
Tokyo Institute of Technology
Kei SAKAGUCHI
Tokyo Institute of Technology
Kiyomichi ARAKI
Tokyo Institute of Technology
Keyword
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Hiroyuki KAMATA, Gia Khanh TRAN, Kei SAKAGUCHI, Kiyomichi ARAKI, "Robust and Low Complexity Bandwidth and Carrier Frequency Estimation for Cognitive Radio" in IEICE TRANSACTIONS on Communications,
vol. E99-B, no. 2, pp. 499-506, February 2016, doi: 10.1587/transcom.2015EBP3265.
Abstract: Cognitive radio (CR) is an important technology to provide high-efficiency data communication for the IoT (Internet of Things) era. Signal detection is a key technology of CR to detect communication opportunities. Energy detection (ED) is a signal detection method that does not have high computational complexity. It, however, can only estimate the presence or absence of signal(s) in the observed band. Cyclostationarity detection (CS) is an alternative signal detection method. This method detects some signal features like periodicity. It can estimate the symbol rate of a signal if present. It, however, incurs high computational complexity. In addition, it cannot estimate the symbol rate precisely in the case of single carrier signal with a low Roll-Off factor (ROF). This paper proposes a method to estimate coarsely a signal's bandwidth and carrier frequency from its power spectrum with lower computational complexity than the CS. The proposed method can estimate the bandwidth and carrier frequency of even a low ROF signal. This paper evaluates the proposed method's performance by numerical simulations. The numerical results show that in all cases the proposed coarse bandwidth and carrier frequency estimation is almost comparable to the performance of CS with lower computational complexity and even outperforms in the case of single carrier signal with a low ROF. The proposed method is generally effective for unidentified classification of the signal i.e. single carrier, OFDM etc.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2015EBP3265/_p
Copy
@ARTICLE{e99-b_2_499,
author={Hiroyuki KAMATA, Gia Khanh TRAN, Kei SAKAGUCHI, Kiyomichi ARAKI, },
journal={IEICE TRANSACTIONS on Communications},
title={Robust and Low Complexity Bandwidth and Carrier Frequency Estimation for Cognitive Radio},
year={2016},
volume={E99-B},
number={2},
pages={499-506},
abstract={Cognitive radio (CR) is an important technology to provide high-efficiency data communication for the IoT (Internet of Things) era. Signal detection is a key technology of CR to detect communication opportunities. Energy detection (ED) is a signal detection method that does not have high computational complexity. It, however, can only estimate the presence or absence of signal(s) in the observed band. Cyclostationarity detection (CS) is an alternative signal detection method. This method detects some signal features like periodicity. It can estimate the symbol rate of a signal if present. It, however, incurs high computational complexity. In addition, it cannot estimate the symbol rate precisely in the case of single carrier signal with a low Roll-Off factor (ROF). This paper proposes a method to estimate coarsely a signal's bandwidth and carrier frequency from its power spectrum with lower computational complexity than the CS. The proposed method can estimate the bandwidth and carrier frequency of even a low ROF signal. This paper evaluates the proposed method's performance by numerical simulations. The numerical results show that in all cases the proposed coarse bandwidth and carrier frequency estimation is almost comparable to the performance of CS with lower computational complexity and even outperforms in the case of single carrier signal with a low ROF. The proposed method is generally effective for unidentified classification of the signal i.e. single carrier, OFDM etc.},
keywords={},
doi={10.1587/transcom.2015EBP3265},
ISSN={1745-1345},
month={February},}
Copy
TY - JOUR
TI - Robust and Low Complexity Bandwidth and Carrier Frequency Estimation for Cognitive Radio
T2 - IEICE TRANSACTIONS on Communications
SP - 499
EP - 506
AU - Hiroyuki KAMATA
AU - Gia Khanh TRAN
AU - Kei SAKAGUCHI
AU - Kiyomichi ARAKI
PY - 2016
DO - 10.1587/transcom.2015EBP3265
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2016
AB - Cognitive radio (CR) is an important technology to provide high-efficiency data communication for the IoT (Internet of Things) era. Signal detection is a key technology of CR to detect communication opportunities. Energy detection (ED) is a signal detection method that does not have high computational complexity. It, however, can only estimate the presence or absence of signal(s) in the observed band. Cyclostationarity detection (CS) is an alternative signal detection method. This method detects some signal features like periodicity. It can estimate the symbol rate of a signal if present. It, however, incurs high computational complexity. In addition, it cannot estimate the symbol rate precisely in the case of single carrier signal with a low Roll-Off factor (ROF). This paper proposes a method to estimate coarsely a signal's bandwidth and carrier frequency from its power spectrum with lower computational complexity than the CS. The proposed method can estimate the bandwidth and carrier frequency of even a low ROF signal. This paper evaluates the proposed method's performance by numerical simulations. The numerical results show that in all cases the proposed coarse bandwidth and carrier frequency estimation is almost comparable to the performance of CS with lower computational complexity and even outperforms in the case of single carrier signal with a low ROF. The proposed method is generally effective for unidentified classification of the signal i.e. single carrier, OFDM etc.
ER -
English
