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OFDM modulation classification dataset
- Citation Author(s):
-
ChongLin
- Submitted by:
- Chong Lin
- Last updated:
- Tue, 05/17/2022 - 22:21
- DOI:
- 10.21227/xwk3-t431
- Link to Paper:
- License:
3170 Views- Categories:
Abstract
This dataset was used for OFDM Signal Real-Time Modulation Recognition Based on Deep Learning and Software-Defined Radio, which provides additional details and description of the dataset. We generate 6 modulated OFDM baseband signals with header modulation and payload modulation as BPSK+BPSK, BPSK+QPSK, BPSK+8PSK, QPSK+BPSK, QPSK+QPSK, QPSK+8PSK, respectively. The SNR range of each signal is from -10 dB to +20 dB at intervals of 2 dB. There are 4096 pieces of data generated for each signal type under a specific SNR and each piece of data has 1024 samples. That is, 6×16×4096 = 393216 pieces in total.
This dataset was used for OFDM Signal Real-Time Modulation Recognition Based on Deep Learning and Software-Defined Radio, which provides additional details and description of the dataset. We generate 6 modulated OFDM baseband signals with header modulation and payload modulation as BPSK+BPSK, BPSK+QPSK, BPSK+8PSK, QPSK+BPSK, QPSK+QPSK, QPSK+8PSK, respectively. The SNR range of each signal is from -10 dB to +20 dB at intervals of 2 dB. There are 4096 pieces of data generated for each signal type under a specific SNR and each piece of data has 1024 samples. That is, 6×16×4096 = 393216 pieces in total.
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Comments
Thank you for developing this dataset.
Thank you for developing this dataset.
Thank you for developing this dataset.
Thank you for developing this dataset.