System for performing semantic communication
AssigneeUniversity-Industry Cooperation Group of Kyung Hee University
InventorsCHOONG SEON HONG, NGUYEN XUANLOC, JI SU YOON
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Abstract
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.
Claims15
A semantic communication system comprising:
- 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 base station comprising:
- a semantic encoder and a channel encoder for performing semantic communication over a wireless channel in a semantic communication system,
- wherein the semantic encoder uses a first deep learning model to extract features from data to be transmitted and generate semantic information based on the extracted features, and
- the channel encoder uses a second deep learning model to map the semantic information to a signal space and convert the semantic information into a signal transmittable over the wireless channel.
A plurality of user equipment devices (UEs) comprising:
- a channel decoder and a semantic decoder for performing semantic communication over a wireless channel in a semantic communication system,
- wherein the channel decoder uses a third deep learning model to remove noise from a channel signal received over the wireless channel based on channel state information and reconstruct the noise-removed signal into semantic information, and
- the semantic decoder uses a fourth deep learning model to restore data included in the reconstructed semantic information based on the reconstructed semantic information.
Dependencies are inferred from the claim text.