DocumentCode :
555229
Title :
Automatic modulation classification in wireless disaster area emergency network (W-DAEN)
Author :
Rahman, Md Arifur ; Haniz, Azril ; Minseok Kim ; Takada, J.
Author_Institution :
Dept. of Int. Dev. Eng., Tokyo Inst. of Technol., Tokyo, Japan
fYear :
2011
fDate :
1-3 June 2011
Firstpage :
226
Lastpage :
230
Abstract :
Post-disaster situation requires quick and effective rescue efforts by the first responders. Generally the rescue teams use wireless radios for intra-agency communications. Lack of collaboration among different rescue agencies may create interference among the emergency radios. Identification of some physical parameters of these active radios is necessary for collaboration. Carrier frequency and bandwidth can be estimated by spectrum sensing, whereas modulation classification requires further signal processing and classification operations. Processing speed and performance of the classification system can be controlled by appropriate selection of signal parameters, signal processing techniques and the classification algorithms. A wireless disaster area emergency network (W-DAEN) can be installed in the disaster area to detect and capture data (time samples) of the occupied frequencies. This study consists of some simulation results of a machine learning based cooperative automatic modulation classification technique by using six unique features. The classification performance and processing time of the proposed algorithm is quite satisfactory for real-time classification system.
Keywords :
interference suppression; modulation; radio networks; radiofrequency interference; signal classification; W-DAEN; carrier frequency; emergency radio interference; intraagency communication; machine learning based cooperative automatic modulation classification technique; physical parameter identification; signal classification algorithm; signal parameter selection; signal processing technique; spectrum sensing estimation; wireless disaster area emergency network; wireless radio; Estimation; Feature extraction; Frequency shift keying; Phase shift keying; Time frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), 2011 Sixth International ICST Conference on
Conference_Location :
Osaka
Print_ISBN :
978-1-4577-0140-5
Type :
conf
Filename :
6030781
Link To Document :
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