勾配駆動型枝刈りコルモゴロフ・アーノルドネットワークに基づく超低複雑度ファイバ非線形性補償
Optics letters
|December 15, 2025
まとめ
新しい勾配駆動型枝刈りコルモゴロフ・アーノルドネットワーク（GDP-KAN）は、波長分割多重（WDM）システムにおけるファイバ非線形性を効率的に補償します。この超低複雑度手法は、伝送距離とデータ容量を大幅に向上させます。
科学分野:
- 光通信
- 工学における人工知能
背景:
- ファイバ非線形性は、WDMコヒーレント光システムにおける伝送距離とデータ容量を制限します。
- 従来のニューラルネットワークイコライザーは、高い計算複雑性に悩まされています。
研究 の 目的:
- WDMシステム向けの効率的なファイバ非線形性補償方法を提案すること。
- パフォーマンスを維持しながら計算複雑性を削減すること。
主な方法:
- 学習可能なスプライン活性化関数を利用した勾配駆動型枝刈りコルモゴロフ・アーノルドネットワーク（GDP-KAN）。
- ネットワークのスパシフィケーションのための帰属スコアに基づく勾配駆動型枝刈り戦略。
- 64 GBaud PDM 16-QAM信号を用いた1600 km SSMF over 8-channel WDM伝送による実験的検証。
主要な成果:
- GDP-KANは超低複雑度（300 RMPB）を達成しました。
- 1スパンあたり1デジタルバックプロパゲーション（DBP）を12%の複雑度で0.63 dB Q^2ファクターゲインで上回りました。
- MLPベースのイコライザーと比較してRMPBを68.75%削減しましたが、パフォーマンスの低下はありませんでした。
結論:
- GDP-KANは、WDMシステムにおけるファイバ非線形性補償のための非常に効率的なソリューションを提供します。
- 計算複雑性を大幅に削減しながら、優れたパフォーマンスを達成します。
- 光通信システムの伝送距離とデータ容量の向上を可能にします。
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