4 results about "Channel decoder" patented technology

A semantic communication system includes a base station including a semantic encoder configured to convert data to be transmitted into semantic information and a channel encoder configured to convert the converted semantic information into a channel signal and a plurality of user equipment devices (UEs) including a channel decoder configured to receive the channel signal and decode the channel signal into the semantic information and a semantic decoder configured to decode data included in the decoded semantic information based on the decoded semantic information.

A multi-channel decoder circuit associated with a multi-channel decoder system is disclosed. The multi-channel decoder circuit comprises a distributed decoder circuit comprising a set of unit decoder circuits, each unit decoder circuit configured to receive one or more codewords of a plurality of codewords associated with a plurality of input channels, and decode the one or more codewords. The multi-channel decoder circuit further comprises a distribution controller circuit configured to distribute each incoming codeword of the one or more codewords to the respective unit decoder circuit of the set of unit decoder circuits within the distributed decoder circuit, based on determining a currently available unit decoder circuit within the set of unit decoder circuits.

There is disclosed a channel decoder apparatus (40) for generating a vectorial feature representation as a vectorial feature representation (40a, 45) in a format specific of a source decoder (50), from a sequence of symbols (36), the vectorial feature representation (40a) representing a source signal (1, 5), the channel decoder apparatus being configured to apply at least one channel-decoder neural network, NN (40a, 42), to the sequence of symbols (36) or another representation (46a, 43a, 42a) of the sequence of symbols, thereby generating the vectorial feature representation in the format specific of the source decoder (50). There is disclosed a channel encoder apparatus (30) for encoding a source signal (1) received as a vectorial feature representation (20a, 21a) from a source encoder (20), the vectorial feature representation (20a, 21a) being in a vectorial format specific of the source encoder (20), the channel encoder apparatus (30) being configured to apply at least one channel-encoder neural network, NN (30a), to the vectorial feature representation (20a, 21a) in the vectorial format specific of the source encoder (20) or to another feature representation (22a, 23a, 24a, 25) of the vectorial feature representation (20a, 21a), to provide a sequence of symbols (35) from the vectorial feature representation (20a, 21a) or the other feature representation (22a, 23a, 24a, 25).

This invention relates to the field of wireless communication channel decoding, specifically a channel decoding method and system based on dynamic channel environments. The method includes: acquiring a received signal; performing synchronization, channel estimation, and demodulation processing on the received signal to obtain an initial log-likelihood ratio vector and a channel-related feature matrix; concatenating and normalizing the initial log-likelihood ratio vector and the channel-related feature matrix to obtain a normalized feature matrix; constructing a log-likelihood ratio correction model; inputting the normalized feature matrix into the log-likelihood ratio correction model to obtain a corrected log-likelihood ratio vector; acquiring a pre-set initial value for a scaling factor; calibrating the corrected log-likelihood ratio vector to obtain a final log-likelihood ratio vector; and inputting the final log-likelihood ratio vector into a channel decoder for decoding. This method solves the problems of lack of adaptability and accuracy in existing channel decoding methods based on dynamic channel environments.