Summary
The Internet-of-Things (IoT) will soon represent the main target application of ICs, involving thousands of autonomous devices forming a large communication network for the purpose of exchanging/processing information about the physical world. From a hardware standpoint, the RF wireless transceivers of IoT devices demand the highest possible energy efficiency and a small area to enable inexpensive large-scale integration. Since analog/RF building blocks must be integrated with the mainstream digital technology, new circuit topologies and techniques must be adopted. The time-mode signaling, recently exploited in all-digital PLLs, data converters (the so called time-mode or VCO-based ADCs), opamps and filters, allows the performance of “analog” circuits to improve with the technology scaling. The proposed research focuses on a novel architecture of time-mode ADC, attempting to mitigate the fundamental limitations of such class of converters (i.e. the highly nonlinear VCO) by exploiting advanced RF techniques, thus giving rise to a hybrid time/frequency-mode operation. Studies have shown that by injection-locking an oscillator to its own delayed resonating waveform (self-injection-locking, SIL), the oscillating frequency can be made reasonably linear versus only two well-controlled parameters (i.e. the amplitude and phase of the self-injected signal). The SIL technique will be exploited to achieve a known, predictable relationship between the oscillating frequency and a certain analog quantity (i.e. the input signal). Accordingly, the proposed research attempts to mathematically overcome, and not to compensate accordingly, the nonlinear characteristic of an oscillator. By adding a simple digital frequency detector, SILICON has potential to devise a new class of data converters, the SIL-ADCs. It will also provide the applicant with cutting edge training from academic & industry leaders in the field which will be implemented using a personalised career development plan.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/747585 |
| Start date: | 01-04-2017 |
| End date: | 31-03-2019 |
| Total budget - Public funding: | 175 866,00 Euro - 175 866,00 Euro |
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Original description
The Internet-of-Things (IoT) will soon represent the main target application of ICs, involving thousands of autonomous devices forming a large communication network for the purpose of exchanging/processing information about the physical world. From a hardware standpoint, the RF wireless transceivers of IoT devices demand the highest possible energy efficiency and a small area to enable inexpensive large-scale integration. Since analog/RF building blocks must be integrated with the mainstream digital technology, new circuit topologies and techniques must be adopted. The time-mode signaling, recently exploited in all-digital PLLs, data converters (the so called time-mode or VCO-based ADCs), opamps and filters, allows the performance of “analog” circuits to improve with the technology scaling. The proposed research focuses on a novel architecture of time-mode ADC, attempting to mitigate the fundamental limitations of such class of converters (i.e. the highly nonlinear VCO) by exploiting advanced RF techniques, thus giving rise to a hybrid time/frequency-mode operation. Studies have shown that by injection-locking an oscillator to its own delayed resonating waveform (self-injection-locking, SIL), the oscillating frequency can be made reasonably linear versus only two well-controlled parameters (i.e. the amplitude and phase of the self-injected signal). The SIL technique will be exploited to achieve a known, predictable relationship between the oscillating frequency and a certain analog quantity (i.e. the input signal). Accordingly, the proposed research attempts to mathematically overcome, and not to compensate accordingly, the nonlinear characteristic of an oscillator. By adding a simple digital frequency detector, SILICON has potential to devise a new class of data converters, the SIL-ADCs. It will also provide the applicant with cutting edge training from academic & industry leaders in the field which will be implemented using a personalised career development plan.Status
CLOSEDCall topic
MSCA-IF-2016Update Date
28-04-2024
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