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

In this paper, we investigate the performance of energy detection-basedspectrum sensing over F composite fading channels. To this end, an analyticalexpression for the average detection probability is firstly derived. Thisexpression is then extended to account for collaborative spectrum sensing,square-law selection diversity reception and noise power uncertainty. Thecorresponding receiver operating characteristics (ROC) are analyzed fordifferent conditions of the average signal-to-noise ratio (SNR), noise poweruncertainty, time-bandwidth product, multipath fading, shadowing, number ofdiversity branches and number of collaborating users. It is shown that theenergy detection performance is sensitive to the severity of the multipathfading and amount of shadowing, whereby even small variations in either ofthese physical phenomena can significantly impact the detection probability. Asa figure of merit to evaluate the detection performance, the area under the ROCcurve (AUC) is derived and evaluated for different multipath fading andshadowing conditions. Closed-form expressions for the Shannon entropy and crossentropy are also formulated and assessed for different average SNR, multipathfading and shadowing conditions. Then the relationship between the Shannonentropy and ROC/AUC is examined where it is found that the average number ofbits required for encoding a signal becomes small (i.e., low Shannon entropy)when the detection probability is high or when the AUC is large. The differencebetween composite and traditional small-scale fading is emphasized by comparingthe cross entropy for Rayleigh and Nakagami-m fading. A validation of theanalytical results is provided through a careful comparison with the results ofsome simulations.

Entropy and Energy Detection-based Spectrum Sensing over F Composite Fading Channels