International Journal of Communications, Network and System Sciences

International Journal of Communications, Network and System Sciences

ISSN Print: 1913-3715
ISSN Online: 1913-3723
www.scirp.org/journal/ijcns
E-mail: ijcns@scirp.org
"Artificial Intelligence Based Model for Channel Status Prediction: A New Spectrum Sensing Technique for Cognitive Radio"
written by Sandhya Pattanayak, Palanaindavar Venkateswaran, Rabindranath Nandi,
published by International Journal of Communications, Network and System Sciences, Vol.6 No.3, 2013
has been cited by the following article(s):
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[1] Cooperative spectrum sensing optimization based adaptive neuro‑fuzzy inference system (ANFIS) in cognitive radio networks
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[2] An optimised neural network-based spectrum prediction scheme for cognitive radio
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[3] Survey of Artificial Intelligence Approaches in Cognitive Radio Networks
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[4] Scalable and Robust ANN Based Cooperative Spectrum Sensing for Cognitive Radio Networks
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[5] Probability Density Function Estimation in OFDM Transmitter and Receiver in Radio Cognitive Networks based on Recurrent Neural Network
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[6] Modeling and Prediction Primary Nodes in Wireless Networks of Cognitive Radio Using Recurrent Neural Networks
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[7] Machine Learning Applied to an RF Communication Channel
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[8] Implementation of a machine learning based modulation scheme in GNURadio for over-the-air packet communications
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[9] Implementación de un modelo predictor para la toma de decisiones en redes inalámbricas de radio cognitiva
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[10] From Sensing to Predictions and Database Technique
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[11] From Sensing to Predictions and Database Technique: A Review of TV White Space Information Acquisition in Cognitive Radio Networks
Wireless Personal Communications, 2017
[12] Primary user characterization for cognitive radio wireless networks using a neural system based on Deep Learning
Artificial Intelligence Review, 2017
[13] Estimation of Future Occupation of Spectral Channels by Licensed Users in Cognitive Radio Networks Applying Neuro-Fuzzy Models
2017
[14] Soft Decision based Spectrum Sensing for Cognitive Radio Networks
International Journal of Digital Application & Contemporary Research, 2015
[15] Identification of spectrum holes using ANN model in TV bands with AWGN
Wireless and Mobile, 2014 IEEE Asia Pacific Conference on, 2014
[16] Spectrum hole detection in TV band using ANN model for opportunistic radio communication
India Conference (INDICON), 2014 Annual IEEE, 2014
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