Related Experiment Video
Updated: Jun 6, 2025

13:39
Optical Trapping of Nanoparticles
Published on: January 15, 2013
22.3K
Dual-wavelength sub-Nyquist sampling scheme for clipping-avoidance photonic ADC.
Optics Letters
|November 27, 2024
Summary
A novel dual-wavelength scheme prevents clipping in photonic analog-to-digital converters (PADCs) by using phase modulation and a Chinese Remainder Theorem (CRT) algorithm. This enables accurate signal reconstruction at sub-Nyquist sampling rates.
Area of Science:
- Photonics
- Electrical Engineering
- Signal Processing
Background:
- Photonic analog-to-digital converters (PADCs) face challenges with signal clipping, especially at high sampling rates.
- Sub-Nyquist sampling offers advantages in reduced hardware complexity and power consumption.
- Existing methods for clipping avoidance in PADCs often require complex circuitry or specific operating conditions.
Purpose of the Study:
- To propose and experimentally validate a dual-wavelength scheme for clipping-avoidance in PADCs operating at sub-Nyquist sampling rates.
- To leverage the phase-wrapping and wavelength-sensitive properties for effective modulo operation.
- To enable reliable signal reconstruction independent of the sampling rate.
Main Methods:
- A dual-wavelength scheme employing phase modulation and a dual-modulus (DM) modulo operation was developed.
- An unwrapping algorithm based on the Chinese Remainder Theorem (CRT) was integrated for signal reconstruction.
- Proof-of-concept experiments were conducted on a PADC chip fabricated on a Lithium Niobate on Insulator (LNOI) platform.
Main Results:
- The proposed scheme successfully avoided clipping in the PADC.
- 1G/2G/4G-baud 10-level pulse amplitude modulation (PAM-10) waveforms were accurately reconstructed.
- Reconstruction was achieved at sub-Nyquist sampling rates of 1/2/4 Gs/s, demonstrating the scheme's effectiveness.
Conclusions:
- The dual-wavelength scheme offers a viable solution for on-chip clipping-avoidance in PADCs.
- The integration of CRT-based unwrapping ensures robust signal reconstruction.
- This approach facilitates high-performance PADC operation at sub-Nyquist sampling rates.
Related Concept Videos
Aliasing
119
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
119
Clipper Circuit
354
A clipper circuit is a fundamental wave-shaping device that harnesses the unique properties of diodes to alter and control waveform characteristics. This technology is widely used in electronic devices, especially in television and radar communication systems, where it enhances waveform modulation in both transmitters and receivers.
The operation of a clipper circuit can be exemplified by analyzing a dual-clipper configuration setup that integrates two ideal diodes, each paired with a biasing...
The operation of a clipper circuit can be exemplified by analyzing a dual-clipper configuration setup that integrates two ideal diodes, each paired with a biasing...
354
Upsampling
204
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
204
Bandpass Sampling
162
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
162
Sampling Theorem
302
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
302

