Numerical Conditional Probability Density Function and Its Application in Jitter Analysis
| Autor: | Dan Oh, Fu Yan, Adam J. Norman, Yunhui Chu, Charles Phares, Alaeddin Aydiner, Oleg Mikulchenko, Beomtaek Lee, Jin Yan, Kai Xiao, Rob Friar |
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| Rok vydání: | 2018 |
| Předmět: |
Stochastic process
Computer science Extrapolation Conditional probability 020206 networking & telecommunications Probability density function 02 engineering and technology Conditional probability distribution Condensed Matter Physics Atomic and Molecular Physics and Optics Computer Science::Performance Histogram 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Algorithm Jitter Communication channel |
| Zdroj: | IEEE Transactions on Electromagnetic Compatibility. 60:1111-1120 |
| ISSN: | 1558-187X 0018-9375 |
| DOI: | 10.1109/temc.2018.2790348 |
| Popis: | Jitter is a critical factor in the performance of high-speed I/O links. Jitter can be modeled as a discrete-time random process. Both the probability density function (PDF) and the spectral characteristics of jitter are important for evaluating its impact on channel performance. The concept of numerical conditional PDF and a new statistical method called FastBER are proposed in this paper to accurately and efficiently perform bit-error-rate (BER) analysis while taking into account both the PDF and the spectral characteristics of an arbitrary jitter sequence for arbitrarily low BER levels. The proposed method achieves the accuracy and flexibility of a transient approach with the high efficiency of a statistical approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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