English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Censoring has been proposed to be utilized in wireless distributed detectionnetworks with a fusion center to enhance network performance in terms of errorprobability in addition to the well-established energy saving gains. In thispaper, we further examine the employment of censoring in infrastructure-lesscognitive radio networks, where nodes employ binary consensus algorithms totake global decisions regarding a binary hypothesis test without a fusioncenter to coordinate such a process. We show analytically - and verify bysimulations - that censoring enhances the performance of such networks in termsof error probability and convergence times. Our protocol shows performancegains up to 46.6% in terms of average error probability over its conventionalcounterpart, in addition to performance gains of about 48.7% in terms ofaverage energy expenditure and savings up to 50% in incurred transmissionoverhead.

Censoring for Improved Sensing Performance in Infrastructure-less Cognitive Radio Networks