Analysis of Hard-Decision and Soft-Data Fusion Schemes for Cooperative Spectrum Sensing in Rayleigh Fading Channel
Autor: | Pasham Shilpa, Srinivas Nallagonda, Y. Rakesh Kumar |
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Rok vydání: | 2017 |
Předmět: |
Fusion
Computer science Speech recognition 05 social sciences 020206 networking & telecommunications 02 engineering and technology Square (algebra) Cognitive radio 0502 economics and business 0202 electrical engineering electronic engineering information engineering 050211 marketing Maximal-ratio combining Algorithm Fusion center Energy (signal processing) Computer Science::Information Theory Rayleigh fading Communication channel |
Zdroj: | 2017 IEEE 7th International Advance Computing Conference (IACC). |
DOI: | 10.1109/iacc.2017.0057 |
Popis: | This paper investigates the performance of hard-decision and soft-data fusion schemes for a cooperative spectrum sensing (CSS) in noisy-Rayleigh faded channel. Hard-decision fusion operations on the local binary decisions and soft-data fusion operations on the energy values obtained from the different cognitive radio (CR) users are performed at fusion center (FC)and a final decision on the status of a primary user (PU) is made. More precisely, the performance of CSS with various hard-decision fusion schemes (OR-rule, AND-rule, and majority-rule) and soft-data fusion schemes (square law selection (SLS), maximal ratio combining (MRC), square law combining (SLC), and selection combining (SC)) is analyzed in this work. Towardsthat, novel and closed-form analytic expressions are derived for probability of detection under all soft schemes in Rayleigh fading channel. A comparative performance between hard-decision and soft-data fusion schemes has been illustrated for different network parameters: time-band width product, average sensingchannel signal-to-noise ratio (SNR), and detection threshold. The optimal detection thresholds for which minimum total error rate is obtained for both soft and hard schemes are also indicated. |
Databáze: | OpenAIRE |
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