Numerical conditional probability density function and its application in jitter analysis
| Autor: | Beomtaek Lee, Rob Friar, Charles Phares, Yunhui Chu, Adam J. Norman, Alaeddin Aydiner, Kai Xiao, Oleg Mikulchenko, Dan Oh |
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| Rok vydání: | 2017 |
| Předmět: |
Sequence
Computer science Stochastic process 020206 networking & telecommunications Probability density function 02 engineering and technology Conditional probability distribution Signal Computer Science::Performance 0202 electrical engineering electronic engineering information engineering Electronic engineering Bit error rate Algorithm Jitter Communication channel |
| Zdroj: | 2017 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI). |
| DOI: | 10.1109/isemc.2017.8077908 |
| Popis: | Jitter is a critical factor to the performance of highspeed signal links. Jitter can be modeled as a random process. Both the probability density function (PDF) and the spectral characteristics of the jitter are important for evaluating the impact to the channel performance. The concept of numerical conditional probability density function (NCPDF) and a new statistical method called FastBER are proposed in this paper to accurately and efficiently perform the bit-error-rate (BER) analysis with taking into account both the PDF and the spectral characteristics of an arbitrary jitter sequence for arbitrarily low BER levels. |
| Databáze: | OpenAIRE |
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