Transceiver decoding method and system based on protograph differential chaos shift keying

A transceiver decoding method based on protograph differential chaos shift keying, a transceiver comprising a protograph differential chaos shift keying transmitter, a wireless channel, a target extrinsic information-aided network and an a-priori calculation decoder, wherein the method comprises:

• acquiring an information bit sequence, performing a coded modulation on the information bit sequence via the protograph differential chaos shift keying transmitter, and outputting a plurality of modulated symbols;
• inputting each modulated symbol into the wireless channel for channel interference, and outputting a received symbol corresponding to each modulated symbol;
• using the target extrinsic information-aided network to determine a target a-posteriori probability vector corresponding to each received symbol according to each received symbol and a preset initial a-posteriori probability vector corresponding to each received symbol;
• inputting each target a-posteriori probability vector into the a-priori calculation decoder for decoding, and outputting an initial decoded bit sequence;
• and
• determining a target decoded bit sequence according to the initial decoded bit sequence and a preset check matrix;
• and
• the target extrinsic information-aided network comprises a convolutional neural network-long short-term memory block, a fully connected block, and a decision block;
• and the step of using the target extrinsic information-aided network to determine a target a-posteriori probability vector corresponding to each received symbol according to each received symbol and a preset initial a-posteriori probability vector corresponding to each received symbol comprises:
• using the convolutional neural network-long short-term memory block to perform one-dimensional feature extraction on each received symbol, and generating a first feature vector corresponding to each received symbol;
• using the fully connected block to perform vector feature extraction on the preset initial a-posteriori probability vector corresponding to each received symbol, and determining a second feature vector corresponding to each preset initial a-posteriori probability vector;
• and
• inputting each first feature vector and each second feature vector into the decision block for feature concatenating separately, and outputting the target a-posteriori probability vector corresponding to each received symbol.