Statistical Integrated Circuit Design

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: closed (15 December 2020) | Viewed by 3948

Special Issue Editor


E-Mail Website
Guest Editor
Department of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, AN, Italy
Interests: statistical integrated circuit design and device modeling; mixed-signal and RF circuit design; nanoelectronics and nanodevices; biomedical circuits and systems; bio-signal analysis and classification; signal processing; neural networks; system identification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advances in electron device fabrication technology to obtain tiny, fast, and low-power integrated circuits (ICs) have caused continuous reduction in the feature size of the devices.

Therefore, at the nanometer geometries used in current technologies, investigating the statistical behavior of integrated devices becomes of paramount importance in IC design.

The scaling of feature size has progressed more rapidly than the scaling of process tolerances, so that with the entrance of the device scaling in the nanometer realm, advanced CMOS devices have been increasingly affected by process variations.

To assess and reduce the impact of these variations on IC performance, systematic and statistical variations across the die must be accurately modeled and simulated at both device and circuit levels.

The aim of this Special Issue is to publish original research articles that cover recent advances in the theory and application of statistical design of ICs.

Potential topics include, but are not limited to, the following:

  • Atomistic level device modeling;
  • Device mismatch modeling;
  • IC design strategies at schematic and layout level;
  • The mathematical approach to stochastic process variations;
  • Mathematical modeling and numerical methods for statistical simulation;
  • The Montecarlo, quasi-Montecarlo, and non-Montecarlo techniques;
  • Parametric yield estimation and minimization;
  • Statistical timing analysis;
  • Statistical simulation tools.

Prof. Dr. Paolo Crippa
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • statistical device modeling
  • statistical timing analysis
  • statistical IC design
  • device variations
  • device mismatch
  • mismatch models
  • clock skew
  • non-Montecarlo simulations
  • parametric yield
  • yield optimization
  • integrated circuit
  • CMOS

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

18 pages, 3860 KiB  
Article
Statistical RF/Analog Integrated Circuit Design Using Combinatorial Randomness for Hardware Security Applications
by Ethan Chen and Vanessa Chen
Mathematics 2020, 8(5), 829; https://doi.org/10.3390/math8050829 - 20 May 2020
Viewed by 3209
Abstract
While integrated circuit technologies keep scaling aggressively, analog, mixed-signal, and radio-frequency (RF) circuits encounter challenges by creating robust designs in advanced complementary metal–oxide–semiconductor (CMOS) processes with the diminishing voltage headroom. The increasing random mismatch of smaller feature sizes in leading-edge technology nodes severely [...] Read more.
While integrated circuit technologies keep scaling aggressively, analog, mixed-signal, and radio-frequency (RF) circuits encounter challenges by creating robust designs in advanced complementary metal–oxide–semiconductor (CMOS) processes with the diminishing voltage headroom. The increasing random mismatch of smaller feature sizes in leading-edge technology nodes severely limit the benefits of scaling for (RF)/analog circuits. This paper describes the details of the combinatorial randomness by statistically selecting device elements that relies on the significant growth in subsets number of combinations. The randomness can be utilized to provide post-manufacturing reconfiguration of the selectable circuit elements to achieve required specifications for ultra-low-power systems. The calibration methodology is demonstrated with an ultra-low-voltage chaos-based true random number generator (TRNG) for energy-constrained Internet of things (IoT) devices in the secure communications. Full article
(This article belongs to the Special Issue Statistical Integrated Circuit Design)
Show Figures

Figure 1

Back to TopTop