JP7181303B2 - ニューラルネットワークを用いた光ファイバ非線形性補償 - Google Patents
ニューラルネットワークを用いた光ファイバ非線形性補償 Download PDFInfo
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- H04B10/6163—Compensation of non-linear effects in the fiber optic link, e.g. self-phase modulation [SPM], cross-phase modulation [XPM], four wave mixing [FWM]
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Description
本出願は、2018年6月22日出願の米国仮特許出願第62/688,456号及び2019年6月21日出願の米国実用新案出願第16/449,319号の優先権を主張するものであり、それらの全内容は、本書で詳細に記載されているかのように参照により組み込まれる。
当業者には理解されるように、ファイバに沿った光学場の展開は、NLSE:
訓練データのセットアップ
Claims (10)
- ニューラルネットワークを使用する光伝送ネットワークのための非線形性補償(NLC)方法(NN-NLC)であって、
前記NN-NLCは、伝送リンクパラメータの知識なしに実行され、
チャネル内相互位相変調(IXPM)およびチャネル内4波混合(IFWM)トリプレットの選択を以下の条件式に基づいて行い、
- 未知のリンクパラメータが、光分散、ファイバ非線形性、およびスパン長からなる群から選択されるものであることを特徴とする、請求項1に記載のNN-NLC方法。
- 前記光伝送ネットワークは、ソフトウェアで定義されたメッシュネットワークであることを特徴とする、請求項2に記載のNN-NLC方法。
- 前記NN-NLCは、訓練段階と実行段階の両方を含むことを特徴とする、請求項3に記載のNN-NLC方法。
- 前記NN-NLC実行段階は、送信リンクの送信側でのみ実行されることを特徴とする、請求項4に記載のNN-NLC方法。
- 前記NN-NLC訓練段階は、受信機のデジタル信号処理装置(DSP)におけるキャリア位相回復から得られたソフトデータ上で動作することを特徴とする、請求項5に記載のNN-NLC方法。
- 前記NN-NLC訓練段階は、学習モデルを生成するために、交差検証(CV)データセットに対してニューラルネットワークモデルの性能を確認することを特徴とする、請求項6に記載のNN-NLC方法。
- 前記学習されたモデルは、前記実行段階における全てのチャネル電力のデータに適用されることを特徴とする、請求項7に記載のNN-NLC方法。
- 訓練段階および実行段階を備えたニューラルネットワークを使用する光ネットワークのための非線形性補償方法であって:
前記訓練段階中に、受信機デジタル信号プロセッサにおける搬送波位相回復からのソフトデータに基づいて動作することによってニューラルネットワークモデルを生成し;
学習されたモデルを生成するために交差検証データセットを用いて前記モデルの性能を評価し;
既知であるがランダムに生成されたパターンを送信し、
ここで、
伝送リンクパラメータの事前の知識なしに、チャネル内相互位相変調(IXPM)およびチャネル内4波混合(IFWM)トリプレットを前記ニューラルネットワークに適用して、非線形性を推定することを含み、
前記IXPM及びIFWMトリプレットの選択を以下の条件式に基づいて行い、
- 前記訓練されたニューラルネットワークモデルは、送信機および受信機の一方に適用される、請求項9に記載の非線形性補償方法。
Applications Claiming Priority (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201862688465P | 2018-06-22 | 2018-06-22 | |
US62/688,465 | 2018-06-22 | ||
US16/449,319 | 2019-06-21 | ||
US16/449,319 US10833770B2 (en) | 2018-06-22 | 2019-06-21 | Optical fiber nonlinearity compensation using neural networks |
PCT/US2019/038638 WO2019246605A1 (en) | 2018-06-22 | 2019-06-24 | Optical fiber nonlinearity compensation using neural networks |
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JP2021513251A JP2021513251A (ja) | 2021-05-20 |
JP7181303B2 true JP7181303B2 (ja) | 2022-11-30 |
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JP (1) | JP7181303B2 (ja) |
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JP7195140B2 (ja) | 2015-08-10 | 2022-12-23 | コーニング インコーポレイテッド | 光学素子の作製方法 |
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US11521055B2 (en) * | 2018-04-14 | 2022-12-06 | International Business Machines Corporation | Optical synapse |
US20210256347A1 (en) * | 2020-01-13 | 2021-08-19 | Nec Laboratories America, Inc | Low complexity fiber nonlinearity compensation using lookup table |
CN111917474B (zh) * | 2020-07-22 | 2022-07-29 | 北京理工大学 | 一种隐式三元组神经网络及光纤非线性损伤均衡方法 |
JP2023544078A (ja) * | 2020-08-18 | 2023-10-20 | クネクト インコーポレイテッド | 機械学習技法を使用して光キャビティを調整するためのシステムおよび方法 |
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CN113595649B (zh) * | 2021-07-19 | 2022-09-30 | 联合微电子中心有限责任公司 | 光学非线性激活单元、方法和光子神经网络 |
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