MSK signal demodulation method based on deep learning under mixed noises
A technology of deep learning and signal demodulation, which is applied in the field of communication, can solve problems such as difficult channel model parameter estimation, and achieve the effects of avoiding pulse parameter estimation, improving soft demodulation accuracy, and good bit error performance
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[0026] The first step is to construct the MSK signal band-pass demodulation network.
[0027] The neural network structure proposed in this embodiment for MSK band-pass signal demodulation under the mixed noise channel is as follows figure 2 shown. The specific structure of each layer of the network is as follows:
[0028] The first layer is the input layer, and the network inputs time_step×T each time b The sampling sequence within a time period, in this embodiment, the value of time_step is 5, and the input size of the network is (5, 30).
[0029] The second layer is the LSTM layer. The output dimension of this layer is 30, and returns a sequence of size (5,30).
[0030] The third layer is the LSTM layer. The output dimension of this layer is 18, and a sequence of size (5,18) is returned.
[0031] The fourth layer is the Reshape layer, which connects the sequence of size (5,18) into a one-dimensional sequence of size 90 by row.
[0032] The fifth layer is a fully conne...
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