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Information Rates of Successive Interference Cancellation for Optical Fiber

Alex Jäger, Gerhard Kramer

TL;DR

This work addresses the challenge of approaching joint-detection performance in nonlinear optical-fiber channels by introducing a practical SIC-based receiver paired with multistage encoding. By leveraging a CPAN surrogate model and Gaussian-message belief propagation on factor graphs, the authors derive scalable detectors that progressively close the gap to JDD as the number of SIC stages $S$ increases, while maintaining linear complexity in $S$. They demonstrate that for Gaussian inputs, 8–16 stages substantially recover JDD-like AIRs, with 32 rings in ring constellations achieving comparable performance to Gaussian signaling at adequate stage counts. The results validate the SIC approach as a viable path toward memoryless-channel-friendly coded modulation in fiber optics, and outline extensions to multi-polarization, space-division multiplexing, and lumped amplification, as well as potential reframing of phase-noise and nonlinear interference compensation.

Abstract

Joint detection and decoding (JDD) achieves rates based on information theory but is too complex to implement for many channels with memory or nonlinearities. Successive interference cancellation (SIC) at the receiver, combined with multistage encoding at the transmitter, is a method that lets one use coded modulation for memoryless channels to approach JDD rates. A SIC-based receiver is presented to compensate for inter-channel interference in long-haul optical fiber links. Simulations for 1000 km of standard single-mode fiber with ideal distributed Raman amplification, single-polarization transmission, and circularly symmetric complex Gaussian (CSCG) modulation show that SIC attains the achievable information rates (AIRs) of JDD using surrogate channel models with correlated phase and additive noise (CPAN). Moreover, the AIRs of ring constellations are compared to those of CSCG modulation. Simulations show that 32 rings, 16 SIC-stages, and Gaussian message passing on the factor graph of the CPAN surrogate model achieve the JDD rates of CSCG modulation. The computational complexity scales in proportion to the number of SIC-stages, where one stage has complexity similar to separate detection and decoding.

Information Rates of Successive Interference Cancellation for Optical Fiber

TL;DR

This work addresses the challenge of approaching joint-detection performance in nonlinear optical-fiber channels by introducing a practical SIC-based receiver paired with multistage encoding. By leveraging a CPAN surrogate model and Gaussian-message belief propagation on factor graphs, the authors derive scalable detectors that progressively close the gap to JDD as the number of SIC stages increases, while maintaining linear complexity in . They demonstrate that for Gaussian inputs, 8–16 stages substantially recover JDD-like AIRs, with 32 rings in ring constellations achieving comparable performance to Gaussian signaling at adequate stage counts. The results validate the SIC approach as a viable path toward memoryless-channel-friendly coded modulation in fiber optics, and outline extensions to multi-polarization, space-division multiplexing, and lumped amplification, as well as potential reframing of phase-noise and nonlinear interference compensation.

Abstract

Joint detection and decoding (JDD) achieves rates based on information theory but is too complex to implement for many channels with memory or nonlinearities. Successive interference cancellation (SIC) at the receiver, combined with multistage encoding at the transmitter, is a method that lets one use coded modulation for memoryless channels to approach JDD rates. A SIC-based receiver is presented to compensate for inter-channel interference in long-haul optical fiber links. Simulations for 1000 km of standard single-mode fiber with ideal distributed Raman amplification, single-polarization transmission, and circularly symmetric complex Gaussian (CSCG) modulation show that SIC attains the achievable information rates (AIRs) of JDD using surrogate channel models with correlated phase and additive noise (CPAN). Moreover, the AIRs of ring constellations are compared to those of CSCG modulation. Simulations show that 32 rings, 16 SIC-stages, and Gaussian message passing on the factor graph of the CPAN surrogate model achieve the JDD rates of CSCG modulation. The computational complexity scales in proportion to the number of SIC-stages, where one stage has complexity similar to separate detection and decoding.
Paper Structure (29 sections, 95 equations, 16 figures, 1 table, 1 algorithm)

This paper contains 29 sections, 95 equations, 16 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. Notation
  4. System Model
  5. CPAN-Model
  6. Factor Graphs and the Sum-Product Algorithm
  7. Generalized Mutual Information
  8. Successive Interference Cancellation
  9. SIC for Gaussian Inputs
  10. Surrogate Based on the CPAN Model
  11. Efficient Computation of the Marginal Distributions
  12. First Stage Detection
  13. Second Stage Detection
  14. Extension to $S$ -Stages
  15. Lower Bounds on Mutual Information
  16. ...and 14 more sections

Figures (16)

  • Figure 1: A node $f(a,b,c)$ and its edges $a,b,c$ in a factor graph.
  • Figure 2: Usage of an equality node.
  • Figure 3: with two stages.
  • Figure 4: Branch of the non-decoded stage. The equality constraint implies $\theta_i=\theta_i'=\theta_i"$. However, the messages of these variables are different in general.
  • Figure 5: Branch of the decoded stage.
  • ...and 11 more figures