Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC Workshops 2013 |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 36-40 |
| Seitenumfang | 5 |
| ISBN (Print) | 9781479901227 |
| Publikationsstatus | Veröffentlicht - 2013 |
| Veranstaltung | 2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC Workshops 2013 - London, Großbritannien / Vereinigtes Königreich Dauer: 8 Sept. 2013 → 9 Sept. 2013 |
Publikationsreihe
| Name | IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC |
|---|
Abstract
This paper presents a robust radio access technology (RAT) classification framework for acquiring comprehensive knowledge on multiple types of coexisting wireless systems. It is built upon the combination of a group of RAT-specific feature metrics using maximum likelihood estimation (MIE) based decision rules. The classification scheme is enhanced by our proposed dimension cancellation (DIC) method for mitigating the noise uncertainty in practical receivers. Based on this framework, a signal classifier for TV white space (TVWS) is designed and implemented which is capable of detecting and classifying DVB-T, 3GPP LTE, IEEE 802.22, ECMA-392 and wireless microphone signals. The classifier is validated by both simulation and real-world experiment using a spectrum sensing testbed. The simulation and experiment performances agree with each other well, which confirms the effectiveness and robustness of the proposed classification scheme. The proposed classification framework will be further applied to our on-going projects kogLTE and ABSOLUTE in which the LTE network is enhanced with cognitive radio for operating in complex radio environment.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
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2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC Workshops 2013. Institute of Electrical and Electronics Engineers Inc., 2013. S. 36-40 6707832 (IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - A robust radio access technology classification scheme with practical considerations
AU - Cao, Hanwen
AU - Jiang, Wei
AU - Wiemeler, Michael
AU - Kaiser, Thomas
AU - Peissig, Jurgen
PY - 2013
Y1 - 2013
N2 - This paper presents a robust radio access technology (RAT) classification framework for acquiring comprehensive knowledge on multiple types of coexisting wireless systems. It is built upon the combination of a group of RAT-specific feature metrics using maximum likelihood estimation (MIE) based decision rules. The classification scheme is enhanced by our proposed dimension cancellation (DIC) method for mitigating the noise uncertainty in practical receivers. Based on this framework, a signal classifier for TV white space (TVWS) is designed and implemented which is capable of detecting and classifying DVB-T, 3GPP LTE, IEEE 802.22, ECMA-392 and wireless microphone signals. The classifier is validated by both simulation and real-world experiment using a spectrum sensing testbed. The simulation and experiment performances agree with each other well, which confirms the effectiveness and robustness of the proposed classification scheme. The proposed classification framework will be further applied to our on-going projects kogLTE and ABSOLUTE in which the LTE network is enhanced with cognitive radio for operating in complex radio environment.
AB - This paper presents a robust radio access technology (RAT) classification framework for acquiring comprehensive knowledge on multiple types of coexisting wireless systems. It is built upon the combination of a group of RAT-specific feature metrics using maximum likelihood estimation (MIE) based decision rules. The classification scheme is enhanced by our proposed dimension cancellation (DIC) method for mitigating the noise uncertainty in practical receivers. Based on this framework, a signal classifier for TV white space (TVWS) is designed and implemented which is capable of detecting and classifying DVB-T, 3GPP LTE, IEEE 802.22, ECMA-392 and wireless microphone signals. The classifier is validated by both simulation and real-world experiment using a spectrum sensing testbed. The simulation and experiment performances agree with each other well, which confirms the effectiveness and robustness of the proposed classification scheme. The proposed classification framework will be further applied to our on-going projects kogLTE and ABSOLUTE in which the LTE network is enhanced with cognitive radio for operating in complex radio environment.
KW - cognitive radio
KW - LTE
KW - OFDM
KW - signal classification
KW - spectrum sensing
KW - TVWS
UR - http://www.scopus.com/inward/record.url?scp=84893629813&partnerID=8YFLogxK
U2 - 10.1109/PIMRCW.2013.6707832
DO - 10.1109/PIMRCW.2013.6707832
M3 - Conference contribution
AN - SCOPUS:84893629813
SN - 9781479901227
T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
SP - 36
EP - 40
BT - 2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC Workshops 2013
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC Workshops 2013
Y2 - 8 September 2013 through 9 September 2013
ER -