IEEE Solid-States Circuits Magazine - Fall 2022 - 28

Vanessa Chen , Jiachen Xu , Yuyi Shen , and Ethan Chen
RF Fingerprint Classification
With CombinatorialRandomness-Based
Power
Amplifiers and Convolutional
Neural Networks
Secure analog/
RF electronics and
electromagnetics
T
28
he growth of the IoT
requires more comprehensive
security
measures than ever. RF
fingerprinting (RFF) utilizes
features in the signals and waveDigital
Object Identifier 10.1109/MSSC.2022.3200302
Date of current version: 11 November 2022
forms from transmitters' physical-layer
imperfections to classify and authenticate
devices. To prevent attacks
from impersonators, combinatorial
randomness is exploited to augment
the RF fingerprints with a high-efficiency
PA for IoT applications. By
enabling different subsets of thinly
sliced PA elements, the transmitter
FALL 2022
IEEE SOLID-STATE CIRCUITS MAGAZINE
can be reconfigured with 220 subsets
that exhibit distinctive RF fingerprints
for signal analysis at the edge. In this
work, a combinatorial-randomnessbased
PA was implemented in a BLE
system. The BLE packets' in-phase
and quadrature samples transmitted
from each configuration are collected
with different SNRs to emulate the
1943-0582/22©2022IEEE
TOP FIGURE:HTTPS://WWW.ECE.CMU.EDU/NEWS-AND-EVENTS/STORY/2022/02/FINGERPRINTING-THE-IOT.HTML

https://orcid.org/0000-0002-9792-5397 https://orcid.org/0000-0001-9798-7419 https://orcid.org/0000-0001-9532-3395 https://orcid.org/0000-0003-4190-6370

IEEE Solid-States Circuits Magazine - Fall 2022

Table of Contents for the Digital Edition of IEEE Solid-States Circuits Magazine - Fall 2022

Contents
IEEE Solid-States Circuits Magazine - Fall 2022 - Cover1
IEEE Solid-States Circuits Magazine - Fall 2022 - Cover2
IEEE Solid-States Circuits Magazine - Fall 2022 - Contents
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IEEE Solid-States Circuits Magazine - Fall 2022 - Cover3
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https://www.nxtbook.com/nxtbooks/ieee/mssc_fall2023
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