6533b7d5fe1ef96bd12651f2

RESEARCH PRODUCT

Contextual neural-network based spectrum prediction for cognitive radio

Jolanta Mizera-pietraszkoMaciej Huk

subject

Cognitive modelComputational modelArtificial neural networkspectrum sensingbusiness.industryTime delay neural networkComputer scienceComputer Science::Neural and Evolutionary Computationartificial intelligenceCognitive networkMachine learningcomputer.software_genrecontextual predictionCognitive radioMultilayer perceptron5G communicationcontextual processingWirelessArtificial intelligencebusinesscomputer

description

Cognitive radio is the technique of effective electromagnetic spectrum usage important for future wireless communication including 5G networks. Neural networks are nature-inspired computational models used to solve cognitive radio prediction problems. This paper presents the use of contextual Sigma-if neural network in prediction of channel states for cognitive radio. Our results indicate that Sigma-if neural network confirms better predictions than Multilayer Perceptron (MLP) network and decreases sensing time for the benefit of the increase of the effectiveness of e-m spectrum usage.

yearjournalcountryeditionlanguage
2015-07-012015 Fourth International Conference on Future Generation Communication Technology (FGCT)
https://doi.org/10.1109/fgct.2015.7393278