Proceedings ArticleDOI
Identification of spectrum holes using ANN model in TV bands with AWGN
Sandhya Pattanayak,Rabindranath Nandi,Palaniandavar Venkateswaran +2 more
- pp 188-193
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TLDR
An artificial neural network model for spectrum sensing in TV band specifically for detecting the presence of audio signals is proposed and tries to remove the disadvantages of conventional energy detection and cyclostationary feature detection technique commonly used for CR applications.Abstract:
Here we propose an artificial neural network (ANN) model for spectrum sensing in TV band specifically for detecting the presence of audio signals. The ANN model is trained with parameters which are a combination of cyclostationary and SNR based features like channel capacity, bandwidth efficiency, autocorrelation. The ANN model is trained with a new decision making factor termed as utilization factor (U) based on the above combination of attributes which lead to a method for detection of spectrum holes. The bandwidth efficiency (η) is also considered as a decision making factor to identify spectrum holes. This unique combination of hypotheses tries to remove the disadvantages of conventional energy detection and cyclostationary feature detection technique commonly used for CR applications.read more
Citations
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Proceedings ArticleDOI
Wireless technology identification using deep Convolutional Neural Networks
TL;DR: A machine learning conduit is developed to facilitate the detection and identification of frequency domain signatures for 802.x standard compliant technologies and results indicate CNN models outperform their counterpart methods in terms of classification accuracy, connoting them to be highly effective tools for detecting and identifying coexisting devices despite acute overlap and interference presence.
Journal Article
Wireless Channel Identification Algorithm Based on Feature Extraction and BP Neural Network.
TL;DR: Different characteristics of wireless channel are extracted based on the arrival time and received signal strength, such as the number of multipath, time delay and delay spread, to establish the feature vector set of wireless channels which is used to train backpropagation (BP) neural network to identify different wireless channels.
Correlation Coefficient Based DVB-T Continual Pilot Detection to Identify Spectrum Hole for CR Application
Mohammad Mizanur Rahman,Chalie Charoenlarpnopparut,Prapun Suksompong,Attaphongse Taparugssanagorn +3 more
TL;DR: A correlation based CP detection which can detect a DVB-T signal at low SNR is proposed and is found from the simulation study for additive white Gaussian noise (AWGN) channel that signal detection at lowSNR is possible compared to the time domain symbol cross-correlation (TDSC) method.
References
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Journal ArticleDOI
A survey of spectrum sensing algorithms for cognitive radio applications
T. Yucek,Huseyin Arslan +1 more
TL;DR: In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented and the cooperative sensing concept and its various forms are explained.
Journal ArticleDOI
Energy detection of unknown deterministic signals
TL;DR: By using Shannon's sampling formula, the problem of the detection of a deterministic signal in white Gaussian noise, by means of an energy-measuring device, reduces to the consideration of the sum of the squares of statistically independent Gaussian variates.
Journal ArticleDOI
On the Energy Detection of Unknown Signals Over Fading Channels
TL;DR: This letter addresses the problem of energy detection of an unknown signal over a multipath channel with the no-diversity case, and presents some alternative closed-form expressions for the probability of detection to those recently reported in the literature.
Book
Wireless Communication
TL;DR: In this article, the authors discuss each block of wireless link in detail including coding, modulation and the advanced topics such as multiplexing, mobile communication, software radio, OFDM and MIMO.