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S-Parameter and Frequency Identification Method for ANN-Based Eye-Height/Width Prediction

Ambasana, Nikita and Anand, Gowri and Gope, Dipanjan and Mutnury, Bhyrav (2017) S-Parameter and Frequency Identification Method for ANN-Based Eye-Height/Width Prediction. In: IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY, 7 (5). pp. 698-709.

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Official URL: http://dx.doi.org/10.1109/TCPMT.2017.2661065

Abstract

Design and analysis of high-speed SerDes channels primarily deal with ensuring signal integrity (SI) for desired electrical performance. SI is predominantly judged by time domain (TD) metrics: bit error rate (BER), eye-height (EH), and eye-width (EW). With increasing bit rates and stringent BER criteria, TD simulations are becoming compute-time-intensive. A full-factorial, cost-effective design space exploration for SI is made possible by learning-based mapping of frequency-domain S-parameter data to EH/EW. A major challenge in this mapping procedure is the identification of relevant S-parameter data, such as return loss, insertion loss, crosstalks, and the frequency points at which they are sampled. This paper outlines a methodology to identify the critical S-parameters at specific frequency points using information theory-based definition of data relevance using a fast correlation-based filter solution for feature selection. This technique is applied for identifying relevant features for generating artificial neural network-based prediction models of EH/EW within 2.5% accuracy for channels with high data rates and complex topologies.

Item Type: Journal Article
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Additional Information: Copy right for this article belongs to the IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 17 Jun 2017 04:07
Last Modified: 17 Jun 2017 04:07
URI: http://eprints.iisc.ernet.in/id/eprint/57236

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