We propose a joint look-up-table (LUT)-based nonlinear predistortion and digital resolution enhancement scheme to achieve high-speed and low-cost optical interconnects using low-resolution digital-to-analog converters (DACs). The LUT-based predistortion is employed to mitigate the pattern-dependent effect (PDE) of a semiconductor optical amplifier (SOA), while the digital resolution enhancer (DRE) is utilized to shape the quantization noise, lowering the requirement for the resolution of DAC. We experimentally demonstrate O-band intensity modulation and direct detection (IM/DD) transmission of 124-GBd 4 / 6-level pulse-amplitude modulation ( PAM ) -4 / 6 and 112-GBd PAM-8 signals over a 2-km standard single-mode fiber (SSMF) with 3 / 3.5 / 4-bit DACs. In the case of 40-km SSMF transmission with an SOA-based preamplifier, 124-GBd on-off-keying (OOK)/PAM-3/PAM-4 signals are successfully transmitted with 1.5 / 2 / 3-bit DACs. To the best of our knowledge, we have achieved the highest net data rates of 235.3-Gb / s PAM-4, 289.7-Gb / s PAM-6, and 294.7 Gb / s PAM-8 signals over 2-km SSMF, as well as 117.6-Gb / s OOK, 173.8-Gb / s PAM-3, and -231.8 Gb / s PAM-4 signals over 40-km SSMF, employing low-resolution DACs. The experimental results reveal that the joint LUT-based predistortion and DRE effectively mitigate the PDE and improve the signal-to-quantization noise ratio by shaping the noise. The proposed scheme can provide a powerful solution for low-cost IM/DD optical interconnects beyond 200 Gb / s.

Optical networks are evolving toward ultrawide bandwidth and autonomous operation. In this scenario, it is crucial to accurately model and control optical power evolutions (OPEs) through optical amplifiers (OAs), as they directly affect the signal-to-noise ratio and fiber nonlinearities. However, a fundamental contradiction arises between the complex physical phenomena in optical transmission and the required precision in network control. Traditional theoretical methods underperform due to ideal assumptions, while data-driven approaches entail exorbitant costs associated with acquiring massive amounts of data to achieve the desired level of accuracy. In this work, we propose a Bayesian inference framework (BIF) to construct the digital twin of OAs and control OPE in a data-efficient manner. Only the informative data are collected to balance the exploration and exploitation of the data space, thus enabling efficient autonomous-driving optical networks (ADONs). Simulations and experiments demonstrate that the BIF can reduce the data size for modeling erbium-doped fiber amplifiers by 80% and Raman amplifiers by 60%. Within 30 iterations, the optimal controlling performance can be achieved to realize target signal/gain profiles in links with different types of OAs. The results show that the BIF paves the way to accurately model and control OPE for future ADONs.

Data centers, the engines of the global Internet, rely on powerful high-speed optical interconnects. In optical fiber communication, classic direct detection captures only the intensity of the optical field, while the coherent detection counterpart utilizes both phase and polarization diversities at the expense of requiring a narrow-linewidth and high-stability local oscillator (LO). Herein, we propose and demonstrate a four-dimensional Jones-space optical field recovery (4-D JSFR) scheme without an LO. The polarization-diverse full-field receiver structure captures information encoded in the intensity and phase of both polarizations, which can be subsequently extracted digitally. To our knowledge, our proposed receiver achieves the highest electrical spectral efficiency among existing direct detection systems and potentially provides similar electrical spectral efficiency as standard intradyne coherent detection systems. The fully recovered optical field extends the transmission distance beyond the limitations imposed by fiber chromatic dispersion. Moreover, the LO-free advantage makes 4-D JSFR suitable for photonic integration, offering a spectrally efficient and cost-effective solution for massively parallel data center interconnects. Our results may contribute to the ongoing developments in the theory of optical field recovery and the potential design considerations for future high-speed optical transceivers.

Chaotic optical communication has shown large potential as a hardware encryption method in the physical layer. As an important figure of merit, the bit rate–distance product of chaotic optical communication has been continually improved to 30 Gb/s × 340 km, but it is still far from the requirement for a deployed optical fiber communication system, which is beyond 100 Gb/s × 1000 km. A chaotic carrier can be considered as an analog signal and suffers from fiber channel impairments, limiting the transmission distance of high-speed chaotic optical communications. To break the limit, we propose and experimentally demonstrate a pilot-based digital signal processing scheme for coherent chaotic optical communication combined with deep-learning-based chaotic synchronization. Both transmission impairment recovery and chaotic synchronization are realized in the digital domain. The frequency offset of the lasers is accurately estimated and compensated by determining the location of the pilot tone in the frequency domain, and the equalization and phase noise compensation are jointly performed by the least mean square algorithm through the time domain pilot symbols. Using the proposed method, 100 Gb / s chaotically encrypted quadrature phase-shift keying (QPSK) signal over 800 km single-mode fiber (SMF) transmission is experimentally demonstrated. In order to enhance security, 40 Gb / s real-time chaotically encrypted QPSK signal over 800 km SMF transmission is realized by inserting pilot symbols and tone in a field-programmable gate array. This method provides a feasible approach to promote the practical application of chaotic optical communications and guarantees the high security of chaotic encryption.