Optical Triple-Band Multiplexing Enabling Beyond-600 Gb/s Single-Photodiode Reception for Intra-AIDC Interconnects

Generative artificial intelligence (AI) models including GPT, Gemini, and DeepSeek are reshaping embodied agents, temporal prediction, and autonomous driving, demanding a ten-fold annual growth in training FLOPS that Moore’s law can no longer sustain. Consequently, scale-out GPU clusters require >400 Gb/s lane-rate optical interconnects within AI data-centers (AIDCs). Single-photodiode direct detection offers density, latency, and energy advantages, but DAC bandwidth remains limited to around 70 GHz. We present an optical triple-band multiplexing scheme that replaces high-frequency radio frequency (RF) mixers and local oscillators (LOs) with photonic components. A Mach–Zehnder modulator (MZM) generates 80-GBd PS-PAM-20 signal while an in-phase/quadrature (IQ) modulator driven by a wavelength-offset laser creates two independent 35-GBd PS-64-QAM bands. The proposed optical multiplexing method breaks conjugate symmetry and enhances dispersion tolerance of the direct detection system. After 200 m SSMF transmission and single 70-GHz photodiode (PD) detection, digital signal-signal beating interference (SSBI)/cross-beating compensation enables the recovery of net 543.9 Gb/s signal (line rate of 686.6 Gb/s) using only 45-GHz DACs. The optical multiplexing architecture provides a path to beyond-400 Gb/s lanes and demonstrates a scalable, energy-efficient solution for next-generation AI clusters.

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Publication Details

Journal
Photonics
Published
2025-12-24
DOI
https://doi.org/10.3390/photonics13010011
Citations
1
Primary Topic
Optical Network Technologies
Type
article
Field-Weighted Citation Impact
0.73
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article

Optical Triple-Band Multiplexing Enabling Beyond-600 Gb/s Single-Photodiode Reception for Intra-AIDC Interconnects

Weiwei Hu, Xiansong Fang, Chongyu Wang, Xiang Cai et al.
1 citations
Photonics
Optical Network Technologies
0.73
article

Optical Triple-Band Multiplexing Enabling Beyond-600 Gb/s Single-Photodiode Reception for Intra-AIDC Interconnects

Weiwei Hu, Xiansong Fang, Chongyu Wang, Xiang Cai, Lingjun Zhou, Yixiao Zhu, Chenbo Zhang, Yimin Hu, Fan Zhang, Ziheng Zhang
article en
1 citations

Abstract

Generative artificial intelligence (AI) models including GPT, Gemini, and DeepSeek are reshaping embodied agents, temporal prediction, and autonomous driving, demanding a ten-fold annual growth in training FLOPS that Moore’s law can no longer sustain. Consequently, scale-out GPU clusters require >400 Gb/s lane-rate optical interconnects within AI data-centers (AIDCs). Single-photodiode direct detection offers density, latency, and energy advantages, but DAC bandwidth remains limited to around 70 GHz. We present an optical triple-band multiplexing scheme that replaces high-frequency radio frequency (RF) mixers and local oscillators (LOs) with photonic components. A Mach–Zehnder modulator (MZM) generates 80-GBd PS-PAM-20 signal while an in-phase/quadrature (IQ) modulator driven by a wavelength-offset laser creates two independent 35-GBd PS-64-QAM bands. The proposed optical multiplexing method breaks conjugate symmetry and enhances dispersion tolerance of the direct detection system. After 200 m SSMF transmission and single 70-GHz photodiode (PD) detection, digital signal-signal beating interference (SSBI)/cross-beating compensation enables the recovery of net 543.9 Gb/s signal (line rate of 686.6 Gb/s) using only 45-GHz DACs. The optical multiplexing architecture provides a path to beyond-400 Gb/s lanes and demonstrates a scalable, energy-efficient solution for next-generation AI clusters.

PhotonicsVol. 13(1)
Shanghai Jiao Tong University (CN), Peking University (CN)
Affordable and clean energy
Openalex Percentile: Top 20%
Optical Network Technologies
0.73
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