Unlimited Dynamic Range Analog-to-Digital Conversion

Analog-to-digital converters (ADCs) provide the link between continuous-time signals and their discrete-time counterparts, and the Shannon-Nyquist sampling theorem provides the mathematical foundation. Real-world signals have a variable amplitude range, whereas ADCs, by design, have a limited input dynamic range, which results in out-of-range signals getting clipped. In this paper, we propose an unlimited dynamic range ADC (UDR-ADC) that is based on the modulo operation (self-reset feature) to alleviate the problem of clipping. The self-reset feature allows for wrapping of the input amplitudes, which preserves the input dynamic range. We present the signal model and a reconstruction technique to recover the original signal samples from the modulo measurements. We validate the operation of the proposed ADC using circuit simulations in 65 nm complementary metal-oxide-semiconductor (CMOS) process technology. The validation is supplemented by a hardware prototype designed using discrete components. A performance assessment in terms of area, power requirement, and the signal-to-quantization-noise ratio (SQNR) shows that the UDR-ADC outperforms the standard ones.

[1]  R. van de Grift,et al.  An 8-bit video ADC incorporating folding and interpolation techniques , 1987 .

[2]  Youngjoong Joo,et al.  Wide dynamic range CMOS image sensor with pixel level ADC , 2003 .

[3]  Chandra Sekhar Seelamantula,et al.  Wavelet-Based Reconstruction for Unlimited Sampling , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[4]  N. P. van der Meijs,et al.  A 26 $\mu$ W 8 bit 10 MS/s Asynchronous SAR ADC for Low Energy Radios , 2011, IEEE Journal of Solid-State Circuits.

[5]  Jerry D. Gibson,et al.  Digital coding of waveforms: Principles and applications to speech and video , 1985, Proceedings of the IEEE.

[6]  Ramesh Raskar,et al.  Unbounded High Dynamic Range Photography Using a Modulo Camera , 2015, 2015 IEEE International Conference on Computational Photography (ICCP).

[7]  Phillip E Allen,et al.  CMOS Analog Circuit Design , 1987 .

[8]  Ramesh Raskar,et al.  Unlimited Sampling of Sparse Sinusoidal Mixtures , 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

[9]  Maik Moeller,et al.  Cmos Integrated Analog To Digital And Digital To Analog Converters , 2016 .

[10]  Youngjoong Joo,et al.  A simple and robust self-reset CMOS image sensor , 2010, 2010 53rd IEEE International Midwest Symposium on Circuits and Systems.

[11]  Ramesh Raskar,et al.  Unlimited Sampling of Sparse Signals , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[12]  U. Fiedler,et al.  A high-speed 8 bit A/D converter based on a Gray-code multiple folding circuit , 1979, IEEE Journal of Solid-State Circuits.

[13]  Vesa Välimäki,et al.  Aliasing Reduction in Clipped Signals , 2016, IEEE Transactions on Signal Processing.

[14]  R. J. van de Plassche,et al.  A high-speed 7 bit A/D converter , 1979 .

[15]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[16]  A. Papoulis Signal Analysis , 1977 .

[17]  Bing Liu,et al.  An Activity-Triggered 95.3 dB DR $-$75.6 dB THD CMOS Imaging Sensor With Digital Calibration , 2009, IEEE Journal of Solid-State Circuits.

[18]  Pavan Kumar Hanumolu,et al.  A Modulo-Based Architecture for Analog-to-Digital Conversion , 2018, IEEE Journal of Selected Topics in Signal Processing.

[19]  Robert H. Walden,et al.  Analog-to-digital converter survey and analysis , 1999, IEEE J. Sel. Areas Commun..

[20]  Amine Bermak,et al.  A vision sensor with on-pixel ADC and in-built light adaptation mechanism , 2002 .

[21]  Ramesh Raskar,et al.  On unlimited sampling , 2017, 2017 International Conference on Sampling Theory and Applications (SampTA).

[22]  J. Ohta,et al.  An Implantable CMOS Image Sensor With Self-Reset Pixels for Functional Brain Imaging , 2016, IEEE Transactions on Electron Devices.