Generalized Machine Learning Equalization in Coherent Receivers

Dataset underpinning manuscript "Generalized Machine Learning Equalization in Coherent Receivers".

"graph_data.xlsx" is an excel spreadsheet containing the graph data. There are two sheets, "Launch Power" which contains the data in Fig 2a, and "Dispersion" containing the data in Fig 2b. In each sheet, the first column is the X axis and further columns are the Y values.

"train_data.pt" and "val_data.pt" contain the training and validation data used in this paper (testing data was generated at test time). Both were generated in Pytorch 2.1, and can be accessed using the built in "torch.load" function supplied by Pytorch. Each file contains a list of dictionaries with keys "rx_training_sequece", "rx_data_sequence", and "tx_data_symbols", denoting the received training sequence, received data sequence, and transmitted symbols respectively, with the corresponding values being complex tensors.

"training_sequence.pt" contains the pulse-shaped training sequence, generated in Pytorch 2.1 and can be accessed in the same way as above, containing a complex tensor.

支撑论文《具有一致接收机的广义机器学习均衡》的数據集。
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""graph_data.xlsx"是一個包含圖形數據的Excel工作表。該工作表包含兩個工作表，"發射功率"工作表包含圖2a中的數據，而"色散"工作表則包含圖2b中的數據。在每個工作表中，第一列是X軸，而隨後的列則是Y值。
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""train_data.pt"和"val_data.pt"包含了本文中使用的訓練和驗證數據（測試數據在測試時生成）。這兩個文件均使用Pytorch 2.1生成，並可通過Pytorch提供的內置"torch.load"函數進行訪問。每個文件均包含一個字典列表，其中的鍵"rx_training_sequece"、"rx_data_sequence"和"tx_data_symbols"分別表示接收到的訓練序列、接收到的數據序列和傳輸的符號，相應的值為複數張量。
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""training_sequence.pt"包含脉冲形的訓練序列，使用Pytorch 2.1生成，並可與上述方式相同進行訪問，其中包含複數張量。