Terahertz Multiple Access: A Deep Reinforcement Learning Controlled Multihop IRS Topology

Terahertz Multiple Access: A Deep Reinforcement Learning Controlled Multihop IRS Topology

<p dir="ltr">We explore THz communication uplink multi-access with multi-hop Intelligent reflecting surfaces (IRSs) under correlated channels. Our aims are twofold: 1) enhancing the data rate of a desired user while dealing with interference from another user and 2) maximizing the co...

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Bibliographic Details
Main Author: Muhammad Shehab (16904880) (author)
Other Authors: Mohamed Elsayed (3524918) (author), Abdullateef Almohamad (16870074) (author), Ahmed Badawy (6992093) (author), Tamer Khattab (16870086) (author), Nizar Zorba (16888728) (author), Mazen Hasna (16904661) (author), Daniele Trinchero (16904886) (author)
Published: 2024
Subjects:
Engineering
Electrical engineering
Information and computing sciences
Machine learning
Artificial intelligence
multi-access communication
sub-millimeter wave communication
communication system performance
Optimization
Reflection
Wireless communication
Uplink
Propagation losses
Correlation
Array signal processing
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