Deep learning-based joint detection for OFDM-NOMA scheme
Non-orthogonal multiple access (NOMA) technique has drawn much attention in recent
years. It has also been a promising technique for the fifth-generation (5G) wireless …
years. It has also been a promising technique for the fifth-generation (5G) wireless …
Uplink NOMA signal transmission with convolutional neural networks approach
LIN Chuan, C Qing, LI Xianxu - Journal of Systems Engineering …, 2020 - ieeexplore.ieee.org
Non-orthogonal multiple access (NOMA), featuring high spectrum efficiency, massive
connectivity and low latency, holds immense potential to be a novel multi-access technique …
connectivity and low latency, holds immense potential to be a novel multi-access technique …
[HTML][HTML] Multi-user joint detection using bi-directional deep neural network framework in NOMA-OFDM system
Non-orthogonal multiple access (NOMA) has great potential to implement the fifth-
generation (5G) requirements of wireless communication. For a NOMA traditional detection …
generation (5G) requirements of wireless communication. For a NOMA traditional detection …
A deep convolutional-LSTM neural network for signal detection of downlink NOMA system
B Panda, P Singh - AEU-International Journal of Electronics and …, 2023 - Elsevier
Non-orthogonal multiple access (NOMA) techniques have drawn much attention for massive
connectivity, heterogeneous data traffic with ultra-low latency requirements, and ultra-high …
connectivity, heterogeneous data traffic with ultra-low latency requirements, and ultra-high …
[HTML][HTML] A deep learning approach for MIMO-NOMA downlink signal detection
C Lin, Q Chang, X Li - Sensors, 2019 - mdpi.com
As a key candidate technique for fifth-generation (5G) mobile communication systems, non-
orthogonal multiple access (NOMA) has attracted considerable attention in the field of …
orthogonal multiple access (NOMA) has attracted considerable attention in the field of …
Examination of the non-orthogonal multiple access system using long short memory based deep neural network
R Shankar, TV Ramana, P Singh… - Journal of Mobile …, 2022 - journals.riverpublishers.com
This paper investigates deep learning (DL) non-orthogonal multiple access (NOMA)
receivers based on long short-term memory (LSTM) under Rayleigh fading channel …
receivers based on long short-term memory (LSTM) under Rayleigh fading channel …
Deep learning-based joint symbol detection for NOMA
Non-orthogonal multiple access is one of the most important candidates for next-generation
communication systems called 5G and beyond. NOMA provides superiority to multiple …
communication systems called 5G and beyond. NOMA provides superiority to multiple …
Impact of the learning rate and batch size on NOMA system using LSTM-based deep neural network
R Shankar, BK Sarojini, H Mehraj… - The Journal of …, 2023 - journals.sagepub.com
In this work, the deep learning (DL)-based fifth-generation (5G) non-orthogonal multiple
access (NOMA) detector is investigated over the independent and identically distributed (iid) …
access (NOMA) detector is investigated over the independent and identically distributed (iid) …
Deep learning empowered semi-blind joint detection in cooperative NOMA
In this paper, we propose a multi-user symbol detection in cooperative-non-orthogonal
multiple access (C-NOMA) schemes via deep learning (DL). We use a DL-based detection …
multiple access (C-NOMA) schemes via deep learning (DL). We use a DL-based detection …
[HTML][HTML] Deep learning based successive interference cancellation scheme in nonorthogonal multiple access downlink network
In this paper, a deep learning-based successive interference cancellation (SIC) scheme for
use in nonorthogonal multiple access (NOMA) communication systems is investigated …
use in nonorthogonal multiple access (NOMA) communication systems is investigated …