A Survey on Deep Learning Techniques in Wireless Signal Recognition

المؤلفون المشاركون

Li, Xiaofan
Dong, Fangwei
Zhang, Sha
Guo, Weibin

المصدر

Wireless Communications and Mobile Computing

العدد

المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-12، 12ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2019-02-17

دولة النشر

مصر

عدد الصفحات

12

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

Wireless signal recognition plays an important role in cognitive radio, which promises a broad prospect in spectrum monitoring and management with the coming applications for the 5G and Internet of Things networks.

Therefore, a great deal of research and exploration on signal recognition has been done and a series of effective schemes has been developed.

In this paper, a brief overview of signal recognition approaches is presented.

More specifically, classical methods, emerging machine learning, and deep leaning schemes are extended from modulation recognition to wireless technology recognition with the continuous evolution of wireless communication system.

In addition, the opening problems and new challenges in practice are discussed.

Finally, a conclusion of existing methods and future trends on signal recognition is given.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Li, Xiaofan& Dong, Fangwei& Zhang, Sha& Guo, Weibin. 2019. A Survey on Deep Learning Techniques in Wireless Signal Recognition. Wireless Communications and Mobile Computing،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1212184

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Li, Xiaofan…[et al.]. A Survey on Deep Learning Techniques in Wireless Signal Recognition. Wireless Communications and Mobile Computing No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1212184

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Li, Xiaofan& Dong, Fangwei& Zhang, Sha& Guo, Weibin. A Survey on Deep Learning Techniques in Wireless Signal Recognition. Wireless Communications and Mobile Computing. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1212184

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1212184