English

Envelope Control Enabled Probabilistic Shaping for Peak Power Constrained IM DD Systems

Signal Processing 2025-07-25 v1

Abstract

Probabilistic shaping (PS) has attracted significant attention in intensity-modulation and direct-detection (IM-DD) systems. However, due to the unique system model and inherent constraints, the effective application of the PS technique is still an open question in IM-DD systems, particularly in systems with memory effects. In this paper, a novel indirect PS scheme tailored for peak power constrained (PPC) IM-DD systems is proposed. The key idea lies in strategically controlling the signal envelope to mitigate memory-induced impairments, such as nonlinearity, overshoot, peak-to-average power ratio enhancement, etc. The proposed scheme incorporates a dynamic selective mapping (DSLM) mechanism at the transmitter, enabling an untypical bit-to-symbol mapping in which the current symbol is not only determined by the current bits pattern but also by previously generated symbols within a specified memory length. At the receiver side, a turbo equalizer with a modified M-BCJR algorithm is proposed to achieve the recovery of ambiguous bits induced by DSLM. Experimental verification in a 56GBaud PAM8 system demonstrates that the proposed scheme exhibits 1dB receiver sensitivity improvement over 2km single-mode fiber transmission. In addition, the proposed scheme has also been demonstrated to be compatible with the typical probabilistic amplitude shaping architecture, enabling a simple and fine-granularity rate adaptation capability. To the best of our knowledge, this work opens a new sight for the application of the PS technique in PPC IM-DD systems with memory effects.

Keywords

Cite

@article{arxiv.2507.18149,
  title  = {Envelope Control Enabled Probabilistic Shaping for Peak Power Constrained IM DD Systems},
  author = {Dongdong Zou and Wei Wang and Jiawen Yao and Zhongxing Tian and Zeyu Feng and Huan Huang and Fan Li and Gordon Ning Liu and Gangxiang Shen and Yi Cai},
  journal= {arXiv preprint arXiv:2507.18149},
  year   = {2025}
}
R2 v1 2026-07-01T04:16:32.279Z