Titre:	MHM : a novel collaborative spectrum sensing method based on markov-chains and harmonic mean for 5G networks
Auteur(s):	Ferreira, Gabriel de Carvalho Barreto, Priscila América Solís Mendez Rocha, Geraldo P. Caetano, Marcos Fagundes Karvonen, Heikki Vartiainen, Johanna
Assunto::	Sensores Processos de Markov 5G Rádio Acesso dinâmico ao espectro
Date de publication:	jui-2020
Editeur:	IEEE
Référence bibliographique:	FERREIRA, Gabriel et al. MHM: a novel collaborative spectrum sensing method based on markov-chains and harmonic mean for 5G networks. In: 2020 IFIP NETWORKING CONFERENCE (NETWORKING), 2020, Paris. Proceedings [...]. Paris: IEEE, 2020. Disponível em: https://ieeexplore.ieee.org/document/9142763.
Abstract:	Cognitive radios and spectrum sensing are considered fundamental for spectrum optimization in 5G networks. Collaborative spectrum sensing improves detection by collecting data from different nodes and increasing the amount of information available for accurate channel state detection. However, malicious nodes can report wrong information, disturbing the collaborative sensing results and network operation. This paper presents two techniques: (1) a Markov chain-based technique that improves spectrum sensing accuracy while reducing the reporting control traffic; (2) a harmonic mean-based technique that discards less relevant sensing reports, mitigating Byzantine attacks. The two techniques were evaluated in a simulation scenarios based on rural areas. The results show that the proposed techniques increase the accuracy of a classic hard-combining fusion technique, reducing false positives and reporting overhead while improving network resilience to malicious nodes.
metadata.dc.description.unidade:	Instituto de Ciências Exatas (IE) Departamento de Ciência da Computação (IE CIC)
metadata.dc.relation.publisherversion:	https://ieeexplore.ieee.org/document/9142763
Collection(s) :	Trabalhos apresentados em evento

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