Broadband radio-frequency signal processing with neuromorphic photonics

Eric C. Blow; Thomas Ferreira de Lima; Hsuan-Tung Peng; Weipeng Zhang; Chaoran Huang; Bhavin J. Shastri; Paul R. Prucnal

doi:10.1117/12.2614131

2 March 2022 Broadband radio-frequency signal processing with neuromorphic photonics

Eric C. Blow, Thomas Ferreira de Lima, Hsuan-Tung Peng, Weipeng Zhang, Chaoran Huang, Bhavin J. Shastri, Paul R. Prucnal

Author Affiliations +

Proceedings Volume 12019, AI and Optical Data Sciences III; 120190N (2022) https://doi.org/10.1117/12.2614131
Event: SPIE OPTO, 2022, San Francisco, California, United States

Abstract

Microwave photonics and neuromorphic photonics are two parallel research areas which have simultaneously emerged at the forefront of next generation processors. These fields, while initially independent, are naturally converging to a combined silicon photonic platform. An optical processing approach yields wide bandwidth, low latency, and dense interconnection. These photonic systems are capable of supporting applications previously unfeasible. Systems such as photonic cancellers, photonic blind source separation, photonic recurrent neural networks for RF fingerprinting, and photonic neural networks for nonlinear dispersion compensation. This paper will focus on the convergence of microwave photonics and neuromorphic photonics towards an RF optimized machine learning solution. Additionally, this paper investigated the RF noise performance of neuromorphic photonic front-end. The results indicated poor RF performances, leading to the proposal of a balanced linear front-end for noise figure reduction.

Conference Presentation

Citation Download Citation

Eric C. Blow, Thomas Ferreira de Lima, Hsuan-Tung Peng, Weipeng Zhang, Chaoran Huang, Bhavin J. Shastri, and Paul R. Prucnal "Broadband radio-frequency signal processing with neuromorphic photonics", Proc. SPIE 12019, AI and Optical Data Sciences III, 120190N (2 March 2022); https://doi.org/10.1117/12.2614131

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