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

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 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 IIT-Bombay Lecture 38 M. Shojaei Baghini

3 3 Modelling of Quantization Noise LSB size: Δ Figure: Ken Martin’s book e(n) is assumed as random white noise, i.e. uniform distribution across all frequencies. IIT-Bombay Lecture 38 M. Shojaei Baghini

4 4 Digital Filtering of the Noise Figure: Boris Murmann Filtering the noise beyond signal frequency band Total quantization noise power is reduced by the factor • (f s /2)/f B which is called oversampling ratio . IIT-Bombay Lecture 38 M. Shojaei Baghini

5 5 SQNR Improvement by Oversampling 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). IIT-Bombay Lecture 38 M. Shojaei Baghini

6 6 Is Oversampling Enough? Assume f B = 500 KHz and ADC resolution = 8 bits. Target resolution: 14 bits ⇒ Required OSR = 2 (6/0.5) = 4096 ⇒ f s = 4096 × 2 × 0.5 MHz = 4.096 GHz! IIT-Bombay Lecture 38 M. Shojaei Baghini

7 7 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 IIT-Bombay Lecture 38 M. Shojaei Baghini

8 8 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 IIT-Bombay Lecture 38 M. Shojaei Baghini

9 9 Discrete-Time Model NTF: Small magnitude in the signal band (|NTF| ≪ 1) STF: Unity Magnitude in the signal band Figure: Boris Murmann (|STF| ≈ 1) IIT-Bombay Lecture 38 M. Shojaei Baghini

10 10 Discrete-Time Model Using A First Order Filter A(z) |A(z)| ≫ 1 ⇒ |STF| ≈ 1 and |NTF| ≪ 1 in the signal frequency band Delayed input Y(z) = (1-Z -1 ) E(z) + z -1 X(z) IIT-Bombay Lecture 38 M. Shojaei Baghini

11 11 End of Lecture 38 IIT-Bombay Lecture 38 M. Shojaei Baghini