تقرير
Scalable orthogonal delay-division multiplexed OEO artificial neural network trained for TI-ADC equalization
| العنوان: | Scalable orthogonal delay-division multiplexed OEO artificial neural network trained for TI-ADC equalization |
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| المؤلفون: | Zazzi, Andrea, Das, Arka Dipta, Hüssen, Lukas, Negra, Renato, Witzens, Jeremy |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science Physics (Other) |
| مصطلحات موضوعية: | Computer Science - Emerging Technologies, Physics - Optics |
| الوصف: | We propose a new signaling scheme for on-chip optical-electrical-optical artificial neural networks that utilizes orthogonal delay-division multiplexing and pilot-tone based self-homodyne detection. This scheme offers a more efficient scaling of the optical power budget with increasing network complexity. Our simulations, based on a 220 nm SOI silicon photonics technology, suggest that the network can support 31 x 31 neurons, with 961 links and freely programmable weights, using a single 500 mW optical comb and an SNR of 21.3 dB per neuron. Moreover, it features a low sensitivity to temperature fluctuations, ensuring that it can be operated outside of a laboratory environment. We demonstrate the network's effectiveness in nonlinear equalization tasks by training it to equalize a time-interleaved ADC architecture, achieving an ENOB over 4 over the entire 75 GHz ADC bandwidth. We anticipate that this network architecture will enable broadband and low latency nonlinear signal processing in practical settings such as ultra-broadband data converters and real-time control systems. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2305.06040 |
| رقم الأكسشن: | edsarx.2305.06040 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |