Multi-Cell Multi-Beam Prediction Using Auto-Encoder LSTM for mmWave Systems

Millimeter wave (mmWave) systems rely on communication in narrow beams for directional and spatial multiplexing gains. A key challenge in realizing these systems is beam tracking, particularly in environments with high mobility and blockage. Additionally, in wide-area mmWave cellular systems, user e...

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Veröffentlicht in:	IEEE transactions on wireless communications 2022-12, Vol.21 (12), p.10366-10380
Hauptverfasser:	Shah, Syed Hashim Ali, Rangan, Sundeep
Format:	Artikel
Sprache:	eng
Schlagworte:	5G mobile communication Base stations Beam switching beamforming cellular wireless channel prediction Coders dimensionality reduction First principles Long short term memory LSTM Machine learning Millimeter wave (mmWave) communications Millimeter wave communication Millimeter waves Misalignment multi-connectivity Multiplexing Neural networks Predictive methods Ray tracing Switches Tracking
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