Polynomial Model-Based Eye Diagram Estimation Methods for LFSR-Based Bit Streams in PRBS Test and Scrambling
This paper proposes eye diagram estimation methods for linear feedback shift register (LFSR)-based bit streams in pseudorandom binary sequence (PRBS) test and scrambling. The PRBS test uses the LFSR as a random data source; scrambling suppresses the radiated EMI by exclusive-OR (XOR) between the data and the LFSR. Both cases include the LFSR as the last block, thus, the LFSR dominantly determines the eye diagram. This paper introduced the deterministic and statistical eye diagram for the PRBS test and scrambling, respectively. The deterministic eye diagram was verified by comparing to the measurement; the statistical eye diagram was verified by comparing to the transient simulation. We also compared the voltage bathtub curves for the scrambling. The measurement and proposed method were correlated up to the BER of 10-10.
J. Park and J. Kim and S. Park and Y. Kim and G. Park and H. Park and D. Lho and K. Cho and S. Lee and D. Kim and J. Kim, "Polynomial Model-Based Eye Diagram Estimation Methods for LFSR-Based Bit Streams in PRBS Test and Scrambling," IEEE Transactions on Electromagnetic Compatibility, vol. 61, no. 6, pp. 1867-1875, Institute of Electrical and Electronics Engineers (IEEE), Mar 2019.
The definitive version is available at https://doi.org/10.1109/TEMC.2019.2900055
Electrical and Computer Engineering
Keywords and Phrases
Electromagnetic Compatibility (EMC); Electromagnetic Interference (EMI); Eye Diagram; High-Speed Channel; Linear-Feedback Shift Register (LFSR); Pseudorandom Binary Sequence (PRBS); Scrambling; Signal Integrity (SI)
International Standard Serial Number (ISSN)
Article - Journal
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
13 Mar 2019