Mixed-Signal VLSI Design Course Code: EE719 Department: Electrical - - PowerPoint PPT Presentation

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Mixed-Signal VLSI Design Course Code: EE719 Department: Electrical - - PowerPoint PPT Presentation

Nov 09, 2022 227 likes •350 views

Mixed-Signal VLSI Design Course Code: EE719 Department: Electrical Engineering Lecture 38: April 10, 2018 Instructor Name: M. Shojaei Baghini E-Mail ID: mshojaei@ee.iitb.ac.in 1 2 2 Module 49 Resolution Enhancement in ADCs using

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Mixed-Signal VLSI Design Course Code: EE719 Department: Electrical Engineering Lecture 38: April 10, 2018

Instructor Name: M. Shojaei Baghini E-Mail ID: mshojaei@ee.iitb.ac.in

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IIT-Bombay Lecture 38 M. Shojaei Baghini

Module 49 Resolution Enhancement in ADCs using Oversampling

References:

  • Section 18.1, Analog Integrated Circuit Design
  • T. C. Caruson, D. A. Johns and K. W. Martin, 2012
  • Prof. Boris Murmann’s Slides
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IIT-Bombay Lecture 38 M. Shojaei Baghini

Modelling of Quantization Noise

LSB size: Δ

e(n) is assumed as random white noise, i.e. uniform distribution across all frequencies.

Figure: Ken Martin’s book

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IIT-Bombay Lecture 38 M. Shojaei Baghini

Digital Filtering of the Noise

Filtering the noise beyond signal frequency band

  • Total quantization noise power is reduced by the factor

(fs/2)/fB which is called oversampling ratio.

Figure: Boris Murmann

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IIT-Bombay Lecture 38 M. Shojaei Baghini

SQNR = 6.02N + 1.76 + 10log(OSR)

Example: OSR=2

  • SQNR is increased by a factor 2 in linear

scale (3 dB increase in dB scale).

  • Resolution is increased by 0.5 bit.

OSR=4 ⇒ 1 bit extra resolution (6 dB) OSR=16 ⇒ 2 bit extra resolution (12 dB) OSR=64 ⇒ 3 bit extra resolution (18 dB)

  • This is similar to averaging (not precisely

since averaging is not an ideal LPF).

SQNR Improvement by Oversampling

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IIT-Bombay Lecture 38 M. Shojaei Baghini

Is Oversampling Enough?

Assume fB = 500 KHz and ADC resolution = 8 bits. Target resolution: 14 bits ⇒ Required OSR = 2(6/0.5) = 4096 ⇒ fs = 4096 × 2 × 0.5 MHz = 4.096 GHz!

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IIT-Bombay Lecture 38 M. Shojaei Baghini

Module 50 Resolution Enhancement using Oversampling and Noise Shaping

References:

  • Section 18.1, Analog Integrated Circuit Design
  • T. C. Caruson, D. A. Johns and K. W. Martin, 2012
  • Prof. Boris Murmann’s Slides
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IIT-Bombay Lecture 38 M. Shojaei Baghini

Reducing Quantization Noise by High-Pass Filtering of the Noise

  • High-pass filtering of the noise and low-pass filtering of

the quantized signal: Practical concept using feedback

Figure: Boris Murmann

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IIT-Bombay Lecture 38 M. Shojaei Baghini

Discrete-Time Model

Figure: Boris Murmann

NTF: Small magnitude in the signal band (|NTF| ≪ 1) STF: Unity Magnitude in the signal band (|STF| ≈ 1)

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IIT-Bombay Lecture 38 M. Shojaei Baghini

Discrete-Time Model Using A First Order Filter

|A(z)| ≫1 ⇒ |STF| ≈ 1 and |NTF| ≪ 1 in the signal frequency band Y(z) = (1-Z-1) E(z) + z-1X(z) Delayed input A(z)

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IIT-Bombay Lecture 38 M. Shojaei Baghini

End of Lecture 38