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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  • CrossRef
[1] Detección de espectro en banda ancha Sub-Nyquist para redes Radio Cognitiva: compleción de matrices mediante valores semilla
2021
[2] Sub-Nyquist Wideband Spectrum sensing for Cognitive Radio Networks: Matrix Completion via seed values
INGE …, 2021
[3] Cooperative spectrum sensing optimization based adaptive neuro-fuzzy inference system (ANFIS) in cognitive radio networks
Journal of Ambient Intelligence and …, 2020
[4] Cooperative spectrum sensing optimization based adaptive neuro‑fuzzy inference system (ANFIS) in cognitive radio networks
2020
[5] A Survey on Soft Computing Techniques for Spectrum Sensing in a Cognitive Radio Network
2020
[6] Predicting Spectral Opportunities in Cognitive Radio Network based on Neuro-Fuzzy for Bandwidth Optimization
2020
[7] An optimised neural network-based spectrum prediction scheme for cognitive radio
2019
[8] Survey of Artificial Intelligence Approaches in Cognitive Radio Networks
2019
[9] Scalable and Robust ANN Based Cooperative Spectrum Sensing for Cognitive Radio Networks
Wireless Personal Communications, 2018
[10] Probability Density Function Estimation in OFDM Transmitter and Receiver in Radio Cognitive Networks based on Recurrent Neural Network
2018
[11] Modeling and Prediction Primary Nodes in Wireless Networks of Cognitive Radio Using Recurrent Neural Networks
2018
[12] Machine Learning Applied to an RF Communication Channel
2018
[13] Implementation of a machine learning based modulation scheme in GNURadio for over-the-air packet communications
2018
[14] Implementación de un modelo predictor para la toma de decisiones en redes inalámbricas de radio cognitiva
2017
[15] From Sensing to Predictions and Database Technique
2017
[16] From Sensing to Predictions and Database Technique: A Review of TV White Space Information Acquisition in Cognitive Radio Networks
Wireless Personal Communications, 2017
[17] Primary user characterization for cognitive radio wireless networks using a neural system based on Deep Learning
Artificial Intelligence Review, 2017
[18] Estimation of Future Occupation of Spectral Channels by Licensed Users in Cognitive Radio Networks Applying Neuro-Fuzzy Models
2017
[19] Soft Decision based Spectrum Sensing for Cognitive Radio Networks
International Journal of Digital Application & Contemporary Research, 2015
[20] Identification of spectrum holes using ANN model in TV bands with AWGN
Wireless and Mobile, 2014 IEEE Asia Pacific Conference on, 2014
[21] Spectrum hole detection in TV band using ANN model for opportunistic radio communication
India Conference (INDICON), 2014 Annual IEEE, 2014
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