Performance Analysis of Dynamic Threshold Estimation Techniques Based on the One-Tier Cognitive Radio Network

Authors: Aditi Gupta, Adeiza James Onumanyi

Cognitive Radios (CRs) use dynamic threshold estimation (DTE) techniques to better detect primary user signals under noise uncertainty regimes. However, DTE techniques have rarely been compared before, particularly under the one tier CR network (CRN) model, making it difficult to assess their comparative performance characteristics under this regime. Thus, in this paper, we have investigated the performance of some notable DTE methods under the one-tier CRN model. We used the auction game model in our investigation to compare fairly the spectrum efficiency performance of each technique. Our findings show that DTEs generally perform better than the fixed threshold method particularly under unpredictable noise uncertainty regimes. Our results show further that the channel utilization (CU) rate of the fixed threshold method, popularly used by researchers, plummets by 50.26% for a 1 dB increase in the noise uncertainty level, while the CU rate of the DTE techniques interestingly increased by an average of 4%. Our investigation will enable CR Engineers to better understand the performance characteristics of DTE techniques under the one-tier CRN model.


Journal: Journal of Computer and Communications
DOI: 10.4236/jcc.2019.72003(PDF)
Paper Id: 90545 (metadata)

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