An algorithm is described for predicting the probability of success of signal transmission in a wireless communication system using machine learning

DOI10.3103/S0278641922030037OpenAlexW4312671013MaRDI QIDQ2107852

E. A. Bobrov

Publication date: 5 December 2022

Published in: Moscow University Computational Mathematics and Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3103/s0278641922030037

zbMATH Keywords

neural networksmachine learningspectral efficiencyadaptive modulation and codingwireless communication systembeamforming matrix

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Channel models (including quantum) in information and communication theory (94A40) Artificial intelligence (68Txx) Computer science (68-XX)

Uses Software

• Adam

Cites Work

• Degrees of freedom in adaptive modulation: a unified view
• Eigen-Based Transceivers for the MIMO Broadcast Channel With Semi-Orthogonal User Selection
• A survey on concept drift adaptation
• Network MIMO With Linear Zero-Forcing Beamforming: Large System Analysis, Impact of Channel Estimation, and Reduced-Complexity Scheduling

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