Unsupervised Learning for Joint Beamforming Design in RIS-Aided ISAC Systems

It is critical to design efficient beamforming in reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) systems for enhancing spectrum utilization. However, conventional methods often have limitations, either incurring high computational complexity due to iterati...

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Veröffentlicht in:	IEEE wireless communications letters 2024-08, Vol.13 (8), p.2100-2104
Hauptverfasser:	Ye, Junjie, Huang, Lei, Chen, Zhen, Zhang, Peichang, Rihan, Mohamed
Format:	Artikel
Sprache:	eng
Schlagworte:	Array signal processing Beamforming beamforming design Communication channels Complexity Correlation Heuristic methods Image enhancement ISAC Iterative algorithms lightweight network Machine learning Neural networks Performance measurement Reconfigurable intelligent surfaces RIS Sensors Signal to noise ratio Unsupervised learning
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