Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Deep Learning-based Spectral Efficiency Maximization in Massive MIMO-NOMA Systems with STAR-RIS

Authors
Yoga, Perdana R.H.Nguyen, T.-V.Pramitarini, Y.Shim, K.An, B.
Issue Date
1-Jan-2023
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Deep learning neural networks; massive MIMO; NOMA; non-convex optimization; phase shift; power allocation; spectral efficiency; STAR-RIS
Citation
5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023, pp 644 - 649
Pages
6
Journal Title
5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023
Start Page
644
End Page
649
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/31097
DOI
10.1109/ICAIIC57133.2023.10067078
ISSN
0000-0000
Abstract
This paper studies a deep learning-based framework for spectral efficiency maximization problem in massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) systems with simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). We formulate the spectral efficiency maximization with a joint design of power allocation of the users, phase shift matrix of transmission and reflection element at the STAR-RIS. Since the problem is non-convex and power allocation of the users and reflector/transmitter elements at a STAR-RIS are coupled, it is very challenging to solve optimally. We propose a low-complexity iterative algorithm based on the inner approximation (IA) method to solve this problem with guaranteed convergence at a relatively optimal level. For real-time optimization, we design a deep learning (DL) framework to predict the optimal solution of power allocation of users, phase shift matrix of transmission and reflection elements at the STAR-RIS according to distances and channel gains from the base station (BS) to STAR-RIS and from STAR-RIS to users. Simulation results show that the suggested scheme improves the spectral efficiency (SE) compared to the massive MIMO system with direct link and without STAR-RIS. Besides, the DL framework can predict the optimal solution within a short time under the suggested scheme. © 2023 IEEE.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Software and Communications Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher An, Beongku photo

An, Beongku
Graduate School (Software and Communications Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE