Aipowered Fiber Optic System Hits Record 2547 Tbs Speed

Imagine downloading an 8K movie instantaneously, without any waiting time. This futuristic scenario is becoming reality thanks to breakthroughs in optical communication technology. A recent collaboration between FiberHome, China Mobile, and research institutions has achieved a staggering 254.7 terabits per second (Tb/s) data transmission over 200 kilometers of single-mode fiber - setting a new world record through the integration of optical and artificial intelligence technologies.

We are living in an era of explosive data growth. According to IDC projections, global data volume will reach 175-181 zettabytes (ZB) by 2025 - triple the 2020 figure. This surge is driven by emerging technologies including AI large language models, generative AI, and edge computing, all demanding unprecedented data transmission speeds and capacity.

Traditional optical communication systems have struggled to balance capacity, distance, and efficiency. As data demands skyrocket, this equilibrium is breaking down. Optical networks - the backbone of digital infrastructure - face both tremendous opportunities and challenges. If the digital economy is a high-speed train, optical networks are the tracks enabling its progress. Without track upgrades, even the fastest trains cannot reach full potential.

The achievement represents significant advances in three core aspects of optical transmission systems:

• Ultra-High Capacity: By implementing dense wavelength division multiplexing and multi-band (S+C+L) cooperative transmission, researchers expanded spectral bandwidth to 19.8THz - over four times conventional systems. This transforms a single-lane road into a four-lane highway for data. Advanced spectral flattening and hybrid amplification achieved 12.86bit/s/Hz spectral efficiency, packing more data into available bandwidth.
• Exceptional Signal Quality: After 200km transmission, signal quality remained excellent. Polarization multiplexing and probabilistic constellation shaping optimized signal entropy, enhancing stability and interference resistance. Combined amplification techniques including Raman amplification minimized signal attenuation and nonlinear effects.
• AI-Enhanced Transmission: Machine learning algorithms, particularly transfer learning neural network equalization, boosted total throughput by 11.7%. This "smart brain" dynamically optimizes transmission parameters. Unlike traditional digital signal processing, AI enables independent neural network models for each band, correcting nonlinear errors while reducing power consumption.

A key innovation involves using neural networks for fiber transmission error correction. Traditional systems rely on complex mathematical models and hardware circuits to compensate nonlinear effects, with inherent limitations in efficiency and accuracy. AI algorithms perform this task more effectively, like an experienced engineer adjusting parameters in real-time.

The team employed transfer learning to dramatically improve AI training efficiency. While conventional methods require separate neural network training for S, C, and L bands - demanding massive data and time - transfer learning applies C-band experience to S/L bands, reducing data requirements by 70% and cutting training cycles in half. This breakthrough addresses critical challenges in data collection and model deployment, accelerating practical implementation.

Remarkably, S/L band models maintained stable performance despite differing wavelength characteristics, power distributions, and nonlinear environments. The L band achieved 12.3% net data rate improvement with neural network equalization, matching C-band gains. Testing confirmed significant compensation for transceiver nonlinearities including modulator bandwidth limits and amplifier noise. This cross-band, cross-scenario generalization establishes transfer learning as a key enabler for AI in optical communications.

This record-breaking achievement marks a new phase in AI-enhanced optical communication systems. As 6G networks and low-altitude economic applications emerge, future optical networks will require greater capacity, lower latency, and enhanced resilience. The deepening integration of AI and optical technologies promises increasingly intelligent networks capable of supporting global digitalization with ultra-high-speed, ultra-reliable transmission - particularly for intercontinental and transoceanic applications.

With continued advances in multi-band expansion, algorithmic optimization, and hardware integration, optical networks are approaching the petabit era (1 petabit = 1000 terabits). This will establish a robust all-optical foundation for digital economic development, enabling more efficient, convenient, and intelligent connectivity worldwide.