Phase Noise Spectrum and Carrier Power Modeling of High Performance Optomechanical Oscillators

CLEO: 2013 ◽  
2013 ◽  
Author(s):  
Alejandro J. Grine ◽  
Karen E. Grutter ◽  
Tristan O. Rocheleau ◽  
Niels Quack ◽  
Turker Beyazoglu ◽  
...  
Keyword(s):  
Phase Noise ◽  
High Performance ◽  
Noise Spectrum ◽  
Power Modeling

Computation of Phase Noise Spectrum in Optoelectronic Oscillator

2021 ◽  
pp. 1-1
Author(s):  
Abhijit Banerjee ◽  
Larissa Aguiar Dantas de Britto ◽  
Gefeson Mendes Pacheco
Keyword(s):  
Phase Noise ◽  
Noise Spectrum ◽  
Optoelectronic Oscillator

scholarly journals Structure of All-Digital Frequency Synthesiser for IoT and IoV Applications

Electronics ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 29 ◽  
Author(s):  
Marijan Jurgo ◽  
Romualdas Navickas
Keyword(s):  
Phase Noise ◽  
Digital Filter ◽  
High Performance ◽  
Domain Model ◽  
Infinite Impulse Response ◽  
Type I ◽  
Noise Sources ◽  
Digital Frequency ◽  
Digitally Controlled Oscillator ◽  
The Impact

In recent years number of Internet of Things (IoT) services and devices is growing and Internet of Vehicles (IoV) technologies are emerging. Multiband transceiver with high performance frequency synthesisers should be used to support a multitude of existing and developing wireless standards. In this paper noise sources of an all-digital frequency synthesiser are discussed through s-domain model of frequency synthesisers, and the impact of noise induced by main blocks of synthesisers to the overall phase noise of frequency synthesisers is analysed. Requirements for time to digital converter (TDC), digitally controlled oscillator (DCO) and digital filter suitable for all-digital frequency synthesiser for IoT and IoV applications are defined. The structure of frequency synthesisers, which allows us to meet defined requirements, is presented. Its main parts are 2D Vernier TDC based on gated ring oscillators, which can achieve resolution close to 1 ps; multi core LC-tank DCO, whose tuning range is 4.3–5.4 GHz when two cores are used and phase noise is −116.4 dBc/Hz at 1 MHz offset from 5.44 GHz carrier; digital filter made of proportional and integral gain stages and additional infinite impulse response filter stages. Such a structure allows us to achieve a synthesiser’s in-band phase noise lower than −100 dBc/Hz, out-of-band phase noise equal to −134.0 dBc/Hz and allows us to set a synthesiser to type-I or type-II and change its order from first to sixth.

A Low Phase Noise and Low Spurious Frequency Source based on Programmable Frequency Dividers

2014 ◽  
Vol 971-973 ◽  
pp. 310-313
Author(s):  
Chen Liang
Keyword(s):  
Phase Noise ◽  
High Performance ◽  
Low Cost ◽  
High Harmonic ◽  
Phase Detector ◽  
Frequency Resolution ◽  
Harmonic Suppression ◽  
Frequency Dividers ◽  
Frequency Source ◽  
Low Phase Noise

In this paper, based on the programmable frequency dividers HMC394 and AD company's integer PLL chip ADF4107, in the premise of not reducing the phase detector frequency, improved the frequency resolution and effectively inhibits the phase stray. Designed a frequency source with high performance index: high resolution is 10kHz, low phase noise is-91.27dBc/Hz @10kHz, low spurious is less than-60dBc, high harmonic suppression is less than-60dBc,the design method is simple, low cost, flexible control, high performance and widely used.

scholarly journals Joint Effect of Heterogeneous Intrinsic Noise Sources on Instability of MEMS Resonators

2016 ◽  
Vol 19 (2) ◽  
pp. 59
Author(s):  
Olga Jakšić ◽  
Ivana Jokić ◽  
Miloš Frantlović ◽  
Danijela Randjelović ◽  
Dragan Tanasković ◽  
...  
Keyword(s):  
Phase Noise ◽  
Noise Analysis ◽  
Intrinsic Noise ◽  
Noise Spectrum ◽  
Joint Effect ◽  
Noise Sources ◽  
Mems Resonators ◽  
Micro Resonator ◽  
Micro Cantilever ◽  
Nyquist Noise

This article's focus is on the numerical estimation of the overall instability of microelectromechanical-system-based (MEMS) resonators, caused by intrinsic noise mechanisms that are different in nature (electrical, mechanical or chemical). Heterogeneous intrinsic noise sources in MEMS resonators that have been addressed here are Johnson–Nyquist noise, 1/f noise, noise caused by temperature fluctuations and adsorptiondesorption induced noise. Their models are given first (based on analytical modeling or based on empirical expressions with experimentally obtained parameters). Then it is shown how each one contributes to the phase noise, a unique figure of merit of resonators instability. Material dependent constants  and knee position in noise spectrum, needed for empirical formulae referring to 1/f noise, have been obtained experimentally, by measurements of noise of MEMS components produced in the Centre of Microelectronic Technologies of the Institute of Chemistry, Technology and Metallurgy in Belgrade. According to these measurements,  varies in the range from 0.776.10-4 to 2.26.10-4 and cut off frequency for 1/f noise varies from 147 Hz to 1 kHz. The determined values are then used for the modeling of micro-resonator phase noise with electrical origin and overall phase noise of a micro-resonator. Numerical example for calculation of overall phase noise is given for a micro-cantilever, produced by the same technology as measured components. The outlined noise analysis can be easily extended and applied to noise analysis of MEMS resonator of an arbitrary shape.

Phase Noise Measurement and Testing with Delta-Sigma TDC

2015 ◽  
Vol 643 ◽  
pp. 149-155 ◽  
Author(s):  
Yusuke Osawa ◽  
Daiki Hirabayashi ◽  
Naohiro Harigai ◽  
Haruo Kobayashi ◽  
Osamu Kobayashi ◽  
...  
Keyword(s):  
Power Spectrum ◽  
Phase Noise ◽  
High Performance ◽  
Phase Measurement ◽  
Phase Fluctuation ◽  
Noise Measurement ◽  
Measurement Time ◽  
Noise Power ◽  
Delta Sigma ◽  
Measurement And Testing

This paper describes a phase noise measurement and testing technique for a clock using a delta-sigma time-to-digital converter (TDC) and verifies its effectiveness with MATLAB simulations. The proposed technique can be implemented with relatively small circuitry, based on the following: (i) The clock under test (CUT) is a repetitive signal. (ii) The time resolution with CUT and a reference clock can be finer with longer measurement time with the delta-sigma TDC. (iii) The phase noise power spectrum can be calculated from the delta-sigma TDC output data using FFT. High performance spectrum analyzers with long measurement time (several ten seconds order due to average of several-time phase measurement results), which are very costly in mass production testing, are not be needed for phase noise measurement with the proposed technique. Our simulation used the input clock of 1 MHz in several phase fluctuation cases, and we observed that the phase fluctuation spectrum at the expected frequency from TDC output power spectrum obtained by FFT. We also investigated the amount of phase fluctuation with our theoretical calculation, which agrees with the simulation results.

High Performance Nanostructured Silicon Oxide Impedance Biosensor System with Online Noise Spectroscopy Analysis

2014 ◽  
Vol 1064 ◽  
pp. 191-196
Author(s):  
Nirmalya Samanta ◽  
Hrilina Ghosh
Keyword(s):  
Digital Signal Processor ◽  
High Performance ◽  
Silicon Oxide ◽  
Specific Antigen ◽  
Complex Mixture ◽  
Digital Signal ◽  
Noise Spectrum ◽  
Spectroscopy Analysis ◽  
Noise Spectroscopy ◽  
Biosensor System

In this paper, noise spectroscopy has been reported earlier as an efficient tool for enhancing the selectivity of biosensors and the analysis was carried out by desktop spectrum analyzer. There were no reports, however, on the efficacy of this method in complex mixture. We have performed here for the first time, noise spectroscopy analysis on complex mixture of food toxin samples and observed that the first cut-off frequencies are indicative of the fact whether the solution has only specific antigen, mixture of specific and nonspecific antigen or no specific antigen at all. To realize a portable immunosensor, we have developed an electronic interface using digital signal processor (DSP) chip of Microchip Technology which has the embedded Fast Fourier Transform (FFT) algorithm for computation of noise spectrum. The entire system has been successfully demonstrated to detect 0.1 fg/ml aflatoxin B1 (AfB1) from a complex mixture with as high as 1000ng/ml non-specific toxins.

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