The research carried out in this project focuses on the design of Radio Frequency (RF)/digital interfaces
defined by software and managed by artificial neural networks (ANN). These RF/digital interfaces consist of a
analog-to-digital converter (ADC) in the receiver and a digital-to-analog converter (DAC) in the transmitter. The objective is to digitize a
wide spectrum of radio signals with a resolution of 8-12 bits, a programmable bandwidth of 30kHz-300MHz and a
Tunable carrier frequency ranging from 0.4GHz to 6GHz. For this, a new generation of RFdigital interfaces will be developed.
based on Sigma-Delta modulation, as well as an auxiliary RF energy harvesting system (RFEH) integrated on the chip. He
The operation of the circuits will be managed by an ANN in order to identify the energy emitted by wireless devices
nearby devices such as mobile phones and Wi-Fi routers and harvest RF energy based on detected information from the environment
electromagnetic. Although the project will cover aspects related to the entire wireless system, it will emphasize the design of
AI-assisted RF ADC and DAC integrated into nanometer (28nm) CMOS technologies. The project will provide solutions
efficient "on-chip" in various applications related to wireless AIoT, and with specifications found in the
cutting edge of the state of the art. The design of the chips will be supported by a design methodology based on ANN and CAD tools
for the automation and optimization of analog, mixed signal circuits, especially ADCs and DACs.
The project addresses some design challenges towards a more efficient digital transformation, directly linked to the actions
strategic objectives of PEICTI 2021-2023, more specifically with action AE4 "Digital World, Industry, Space and Defense". It is also
aligned with Goal 9 "Industries, Innovation and Infrastructure" of the ONU Sustainable Development Goals (SDGs).
Project PID2022-138078OB-I00 funded by MICIU/AEI /10.13039/501100011033/ and FEDER 'Una manera de hacer Europa'.
