[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 …
Bayesian and multi-armed contextual meta-optimization for efficient wireless radio resource management
Optimal resource allocation in modern communication networks calls for the optimization of
objective functions that are only accessible via costly separate evaluations for each …
objective functions that are only accessible via costly separate evaluations for each …
HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System
Deep learning (DL) techniques can significantly improve successive interference
cancellation (SIC) performance for the non-orthogonal multiple access (NOMA) system. The …
cancellation (SIC) performance for the non-orthogonal multiple access (NOMA) system. The …
Adaptive NOMA-Based Spectrum Sensing for Uplink IoT Networks
With the rapid growth in the requirements of the Internet of Things (IoT), the scarcity of
spectrum resources is becoming serious. Non-orthogonal multiple access (NOMA) and …
spectrum resources is becoming serious. Non-orthogonal multiple access (NOMA) and …
[PDF][PDF] Implementation of the deep learning method for signal detection in massive-MIMO-NOMA systems
The deep learning method (DLM) is one way to fix issues in optical nonorthogonal multiple
access (O-NOMA) systems that are caused by signals that overlap and interfere with each …
access (O-NOMA) systems that are caused by signals that overlap and interfere with each …
Mobile edge computing based cognitive network security analysis using multi agent machine learning techniques in B5G
Y Duan, Q Wu, X Zhao, X Li - Computers and Electrical Engineering, 2024 - Elsevier
The proliferation of wireless applications at an exponential rate has made spectrum
problems worse. Saturation in the unlicensed frequency spectrum is rapidly increasing as a …
problems worse. Saturation in the unlicensed frequency spectrum is rapidly increasing as a …
Artificial intelligence driven cognitive optimization and predictive analysis using blockchain privacy-based machine learning model
Y Qiu, C Zhang - Computers and Electrical Engineering, 2024 - Elsevier
According to the cognitive radio paradigm, spectrum sensing, decision-making, sharing, and
mobility phases can be integrated to enable both authorised and unauthorised users to …
mobility phases can be integrated to enable both authorised and unauthorised users to …
Deep learning-based sequential models for multi-user detection with M-PSK for downlink NOMA wireless communication systems
B Panda, P Singh - Annals of Telecommunications, 2023 - Springer
Non-orthogonal multiple access (NOMA) techniques have the potential to achieve large
connectivity requirements for future-generation wireless communication. NOMA detection …
connectivity requirements for future-generation wireless communication. NOMA detection …
Analytical Analysis of Bit Error Rate Performance of NOMA-OFDM for 5G Systems
S Sahoo - 2023 14th International Conference on Computing …, 2023 - ieeexplore.ieee.org
An analytical approach of the bit error rate (BER) performance of Non-Orthogonal Multiple
Access with Orthogonal Frequency Division Multiplexing (NOMA-OFDM) for 5G …
Access with Orthogonal Frequency Division Multiplexing (NOMA-OFDM) for 5G …