Successive Interference Cancellation for Optical Fiber Transmission Using Discrete Modulation Constellations

Core Concepts

Successive interference cancellation (SIC) can be used to efficiently detect discrete modulation symbols transmitted over a 1000 km fiber-optic link, achieving information rates comparable to previous studies using continuous modulations.

Abstract

The authors investigate communication via wavelength-division multiplexing (WDM) through optical networks, where receivers can only access their own WDM channel. They model the distortions caused by cross-phase modulation (XPM) as phase noise with correlations over many symbols.
The authors propose a receiver design that uses SIC to detect discrete modulation symbols, specifically probabilistically-shaped star quadrature-amplitude modulation (QAM) constellations. The key steps are:

Detect and decode the absolute value of the transmitted symbols using a memoryless detector, passing the information to the next stage.
Detect the phase of the symbols in two stages, using a memoryless detector for the first stage and an approximate message passing algorithm for the second stage.

The authors show that the proposed transmitter and receiver can achieve information rates comparable to previous studies using continuous modulations and a genie-aided receiver that can fully compensate for phase noise. They find that 32 rings and 128 phases are sufficient when using 16 SIC stages, and that 2-4 SIC stages offer a good trade-off between performance and computational cost.
The authors also discuss potential future work, such as incorporating single-channel digital backpropagation to mitigate inter-symbol interference caused by XPM.

Stats

The authors use a 1000 km link with ideal distributed Raman amplification for their simulations.

Quotes

"The proposed transmitter and receiver show competitive performance in mitigating phase noise with long correlations, similar to a genie-aided receiver that can fully compensate for phase noise[11]."
"We found that 32 rings and 128 phases suffice when using 16 SIC-stages. Also, 2-4 SIC-stages offer a good trade-off between performance and computational cost and might hence be interesting for practical implementations."

Key Insights Distilled From

Successive Interference Cancellation for Optical Fiber Using Discrete Constellations

by Alex... at arxiv.org 05-07-2024

https://arxiv.org/pdf/2405.03232.pdf

Deeper Inquiries

How could the receiver design be further improved to achieve even higher information rates, potentially by incorporating more advanced techniques for mitigating inter-symbol interference

To achieve even higher information rates, the receiver design could be enhanced by incorporating more advanced techniques to mitigate inter-symbol interference (ISI). One approach could involve the utilization of advanced equalization techniques such as decision feedback equalization (DFE) or maximum likelihood sequence estimation (MLSE). By implementing these techniques, the receiver can better combat the effects of ISI caused by factors like cross-phase modulation (XPM) in optical fiber communication systems. MLSE, for instance, can effectively estimate the transmitted symbol sequence by considering the inter-symbol interference and noise characteristics in the channel. Additionally, adaptive algorithms like the recursive least squares (RLS) algorithm could be employed to dynamically adjust the equalization parameters based on the changing channel conditions, further improving the system's performance in the presence of ISI.

What are the practical challenges and trade-offs in implementing the proposed SIC-based receiver in a real-world optical fiber communication system

Implementing the proposed SIC-based receiver in a real-world optical fiber communication system poses several practical challenges and trade-offs. One significant challenge is the computational complexity associated with multiple stages of interference cancellation, especially as the number of stages increases to achieve higher information rates. This complexity can impact real-time processing requirements and may necessitate efficient hardware implementations to handle the computational load effectively. Another challenge is the sensitivity to channel impairments and noise, which can degrade the performance of the SIC receiver, particularly in scenarios with high signal-to-noise ratios (SNRs) or severe nonlinear effects like self-phase modulation (SPM).
Trade-offs in implementing the SIC-based receiver include the balance between performance and complexity. While increasing the number of SIC stages can enhance information rates, it also escalates computational demands and hardware costs. Moreover, the trade-off between achievable rates and error correction capabilities must be carefully managed, as aggressive interference cancellation may lead to higher error rates if not appropriately controlled. Overall, the practical implementation of the SIC-based receiver requires a thorough consideration of these challenges and trade-offs to optimize system performance in real-world scenarios.

What other types of discrete modulation constellations could be explored, and how might their performance compare to the probabilistically-shaped star-QAM constellations used in this work

In exploring other types of discrete modulation constellations, researchers could investigate techniques like lattice constellations, amplitude-phase constellations, or geometrically shaped constellations. Lattice constellations offer structured signal sets that can provide improved performance in the presence of channel impairments. Amplitude-phase constellations combine amplitude and phase modulation to enhance spectral efficiency and robustness to noise. Geometrically shaped constellations, such as nested constellations or constellation shaping techniques, aim to optimize the signal space to improve the overall system performance.
Comparing these alternative constellations to the probabilistically-shaped star-QAM constellations used in the study, researchers would need to evaluate factors like spectral efficiency, error performance, and complexity. Each type of constellation has its unique characteristics and trade-offs, such as the complexity of encoding and decoding, sensitivity to channel impairments, and the ability to mitigate inter-symbol interference. By conducting comprehensive performance evaluations and simulations, researchers can determine the suitability of different modulation constellations for specific optical fiber communication scenarios and potentially identify novel approaches to enhance system performance.