Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA

<p dir="ltr">In this work, we examine an intelligent reflecting surface (IRS) assisted downlink non-orthogonal multiple access (NOMA) scenario intending to maximize the sum-rate of users. The optimization problem at the IRS is quite complicated, and non-convex since it requires the t...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Muhammad Shehab (16904880) (author)
مؤلفون آخرون:	Bekir S. Ciftler (16904883) (author), Tamer Khattab (16870086) (author), Mohamed M. Abdallah (8476953) (author), Daniele Trinchero (16904886) (author)
منشور في:	2022
الموضوعات:	Engineering Communications engineering Information and computing sciences Distributed computing and systems software Machine learning NOMA Wireless communication Resource management Downlink Optimization Interference cancellation 6G mobile communication Intelligent reflecting surfaces (IRS) Non-orthogonal multiple access (NOMA) Deep reinforcement learning (DRL) 5G and beyond 6G Phase shift design
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Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA

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