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IJON
2011

Fault tolerant machine learning for nanoscale cognitive radio

12 years 7 months ago
Fault tolerant machine learning for nanoscale cognitive radio
We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanoscale implementation constraints; we do not describe all physical details but believe future physical implementation to be feasible. The system uses analog computation and consists of cyclostationary feature extraction and a radial basis function network for classification. We describe a model for nanoscale faults in the system, and simulate experimental performance and fault tolerance in recognizing WLAN signals, under different levels of noise and computational errors. The system performs well under expected non-ideal manufacturing and operating conditions.
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo
Added 30 Aug 2011
Updated 30 Aug 2011
Type Journal
Year 2011
Where IJON
Authors Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo
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