Enhancing RF Fingerprint Generation in Power Amplifiers: Unequally Spaced Multitone Design Approaches and Considerations
The rapid growth of Internet of Things (IoT) devices and communication standards has led to an increasing demand for data security, particularly with limited hardware resources. In addition to conventional software-level data encryption, physical-layer security techniques, such as device-specific ra...
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of the Solid-State Circuits Society |
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| Online Access: | https://ieeexplore.ieee.org/document/10660491/ |
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| author | Chengyu Fan Junting Deng Ethan Chen Vanessa Chen |
| author_facet | Chengyu Fan Junting Deng Ethan Chen Vanessa Chen |
| author_sort | Chengyu Fan |
| collection | DOAJ |
| description | The rapid growth of Internet of Things (IoT) devices and communication standards has led to an increasing demand for data security, particularly with limited hardware resources. In addition to conventional software-level data encryption, physical-layer security techniques, such as device-specific radio frequency fingerprints (RFFs), are emerging as promising solutions. This article first summarizes prior arts on timestamped RFFs generation and reconfigurable power amplifier (PA) designs. Following that, an innovative 2-stage PA incorporating a reconfigurable class A stage with a Doherty amplifier, designed in 65-nm CMOS to generate 4096 timestamped RFFs without introducing in-band power variation, is presented. Multiple 3-bit resistive digital-to-analog converters (RDACs) are applied to control body biasing units within the two-stage PA, facilitating the generation of massive and distinguishable RFFs. Subsequently, time-varying unequally spaced multitone (USMT) techniques are proposed to further elevate the count of available timestamped RFFs from 4096 to 16 384. The validation results of RFFs utilizing 64-QAM WiFi-6E advertising packets, employing time-varying USMT transmitted within the 5.39–5.41-GHz band, confirm the successful generation of 16 384 distinct RFF patterns. Moreover, the measurement results demonstrate that more than 11 504 RFFs among the generated patterns can be classified with an accuracy exceeding 99%. |
| format | Article |
| id | doaj-art-d1374b5d57d540cfbd0146fc5847bbe6 |
| institution | Kabale University |
| issn | 2644-1349 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Solid-State Circuits Society |
| spelling | doaj-art-d1374b5d57d540cfbd0146fc5847bbe62025-01-25T00:03:18ZengIEEEIEEE Open Journal of the Solid-State Circuits Society2644-13492024-01-014839610.1109/OJSSCS.2024.345140110660491Enhancing RF Fingerprint Generation in Power Amplifiers: Unequally Spaced Multitone Design Approaches and ConsiderationsChengyu Fan0https://orcid.org/0009-0005-6936-4632Junting Deng1https://orcid.org/0009-0002-5059-9915Ethan Chen2https://orcid.org/0000-0001-9532-3395Vanessa Chen3https://orcid.org/0000-0003-4190-6370Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, PA, USAElectrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, PA, USAElectrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, PA, USAElectrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, PA, USAThe rapid growth of Internet of Things (IoT) devices and communication standards has led to an increasing demand for data security, particularly with limited hardware resources. In addition to conventional software-level data encryption, physical-layer security techniques, such as device-specific radio frequency fingerprints (RFFs), are emerging as promising solutions. This article first summarizes prior arts on timestamped RFFs generation and reconfigurable power amplifier (PA) designs. Following that, an innovative 2-stage PA incorporating a reconfigurable class A stage with a Doherty amplifier, designed in 65-nm CMOS to generate 4096 timestamped RFFs without introducing in-band power variation, is presented. Multiple 3-bit resistive digital-to-analog converters (RDACs) are applied to control body biasing units within the two-stage PA, facilitating the generation of massive and distinguishable RFFs. Subsequently, time-varying unequally spaced multitone (USMT) techniques are proposed to further elevate the count of available timestamped RFFs from 4096 to 16 384. The validation results of RFFs utilizing 64-QAM WiFi-6E advertising packets, employing time-varying USMT transmitted within the 5.39–5.41-GHz band, confirm the successful generation of 16 384 distinct RFF patterns. Moreover, the measurement results demonstrate that more than 11 504 RFFs among the generated patterns can be classified with an accuracy exceeding 99%.https://ieeexplore.ieee.org/document/10660491/Combinatorial randomness (CR)Internet of Things (IoT)machine learningneural networkspower amplifier (PA)radio frequency fingerprint (RFF) |
| spellingShingle | Chengyu Fan Junting Deng Ethan Chen Vanessa Chen Enhancing RF Fingerprint Generation in Power Amplifiers: Unequally Spaced Multitone Design Approaches and Considerations IEEE Open Journal of the Solid-State Circuits Society Combinatorial randomness (CR) Internet of Things (IoT) machine learning neural networks power amplifier (PA) radio frequency fingerprint (RFF) |
| title | Enhancing RF Fingerprint Generation in Power Amplifiers: Unequally Spaced Multitone Design Approaches and Considerations |
| title_full | Enhancing RF Fingerprint Generation in Power Amplifiers: Unequally Spaced Multitone Design Approaches and Considerations |
| title_fullStr | Enhancing RF Fingerprint Generation in Power Amplifiers: Unequally Spaced Multitone Design Approaches and Considerations |
| title_full_unstemmed | Enhancing RF Fingerprint Generation in Power Amplifiers: Unequally Spaced Multitone Design Approaches and Considerations |
| title_short | Enhancing RF Fingerprint Generation in Power Amplifiers: Unequally Spaced Multitone Design Approaches and Considerations |
| title_sort | enhancing rf fingerprint generation in power amplifiers unequally spaced multitone design approaches and considerations |
| topic | Combinatorial randomness (CR) Internet of Things (IoT) machine learning neural networks power amplifier (PA) radio frequency fingerprint (RFF) |
| url | https://ieeexplore.ieee.org/document/10660491/ |
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