Abstract
In this letter, an efficient graph neural network (GNN) assisted detector is conceived for the orthogonal time frequency space (OTFS) system. Specifically, the transmit symbols are viewed as the nodes of GNN, obtaining the detection results through aggregation, update, and output modules. Firstly, the aggregation module is employed to weigh the connections between adjacent nodes. Subsequently, the update module amends node features according to the calculated connection value and the node’s information. Finally, after a certain number of iterations, the output module classifies nodes relying on the final features to realize signal detection. Simulation results confirm that the proposed GNN-assisted detector outperforms the latest intelligent detector by around 1 dB.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
