Model-Based Deep Learning Receiver Design for Rate-Splitting Multiple Access
Author:
Affiliation:
1. Department of Electrical and Electronic Engineering, Imperial College London, London, U.K
Funder
Defence Science and Technology Laboratory (Dstl) Communications and Networks Research Programme
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications
Link
http://xplorestaging.ieee.org/ielx7/7693/10314841/10091798.pdf?arnumber=10091798
Reference48 articles.
1. Overloaded multiuser MISO transmission with imperfect CSIT
2. Deep Learning-Based MIMO-NOMA With Imperfect SIC Decoding
3. Linear Precoding and Stream Combining for Rate Splitting in Multiuser MIMO Systems
4. Deep Learning-aided Successive Interference Cancellation for MIMO-NOMA
5. A rate-splitting strategy for max-min fair multigroup multicasting
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