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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper proposes simple moment based spectrum sensing algorithm forcognitive radio networks in a flat fading channel. It is assumed that thetransmitted signal samples are binary (quadrature) phase-shift keying BPSK(QPSK), Mary quadrature amplitude modulation (QAM) or continuous uniformlydistributed random variables and the noise samples are independent andidentically distributed circularly symmetric complex Gaussian random variablesall with unknown (imperfect) variance. Under these assumptions, we propose asimple test statistics employing a ratio of fourth and second moments. For thisstatistics, we provide analytical expressions for both probability of falsealarm (Pf) and probability of detection (Pd) in an additive white Gaussiannoise (AWGN) channel.We confirm the theoretical expressions by computersimulation. Furthermore, under noise variance uncertainty, simulation resultsdemonstrate that the proposed moment based detector gives better detectionperformance compared to that of energy detector in AWGN and Rayleigh fadingchannels.

Moment based Spectrum Sensing Algorithm for Cognitive Radio Networks with Noise Variance Uncertainty