High level modeling of signal integrity in field bus communication with SystemC-AMS

This paper presents a novel method for modeling the functionality of a mixed-signal system, and analyzing its signal integrity (SI) at a high-level of abstraction with SystemC-AMS. Our model includes on a unique platform a functional module and a non-functional module. The functional module represents the operative behavior of the system and the non-functional module, based on neural network techniques, displays the SI characteristics of the system. The proposed method is demonstrated by modeling field bus communication system with two nodes. We achieved an error of about 3% for the neural network based Time Data Flow (TDF) model with respect to a RLC Electrical Linear Networks (ELN) model.

[1]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[2]  S. Grivet-Talocia,et al.  Fast Macromodel-based Signal Integrity Assessment for RF and Mixed-Signal Modules , 2007, 2007 IEEE International Symposium on Electromagnetic Compatibility.

[3]  G. Gielen,et al.  Assessment of the DPI Standard for Immunity Simulation of Integrated Circuits , 2007, 2007 IEEE International Symposium on Electromagnetic Compatibility.

[4]  Junwu Tao,et al.  Modeling the Electromagnetic Emission of a Microcontroller Using a Single Model , 2008, IEEE Transactions on Electromagnetic Compatibility.

[5]  Qi-Jun Zhang,et al.  Neural Networks for RF and Microwave Design , 2000 .

[6]  Gerd Vandersteen,et al.  High-level simulation and modeling tools for mixed-signal front-ends of wireless systems , 2002 .

[7]  Qi-Jun Zhang,et al.  Neural Networks for Microwave Modeling: Model Development Issues and Nonlinear Modeling Techniques , 2001 .

[8]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[9]  Kenneth S. Kundert,et al.  Design of mixed-signal systems-on-a-chip , 2000, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[10]  Martin Barnasconi,et al.  Advancing the SystemC Analog / Mixed-Signal ( AMS ) Extensions Introducing Dynamic Timed Data Flow , 2011 .

[11]  G. Vasilescu,et al.  Electronic Noise and Interfering Signals: Principles and Applications , 2005 .

[12]  François Pêcheux,et al.  Modeling and Refining Heterogeneous Systems With SystemC-AMS: Application to WSN , 2008, 2008 Design, Automation and Test in Europe.

[13]  Martin T. Hagan,et al.  Neural network design , 1995 .

[14]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[15]  Stephen A. Billings,et al.  Non-linear system identification using neural networks , 1990 .

[16]  L. Green,et al.  Signal integrity , 1998, Northcon/98. Conference Proceedings (Cat. No.98CH36264).

[17]  Patrick Garda,et al.  Modelling Field Bus Communications in Mixed-Signal Embedded Systems , 2008, EURASIP J. Embed. Syst..