Ali et al. proposed a physical (PHY) layer resource management for single-carrier N-
antenna beamforming (BF) non-orthogonal multiple access (NOMA) systems. Cross …

In previous study, deep learning and autoencoder have been applied for data detection of
NOMA systems, rather than the resource allocation of OFDMA/NOMA systems. In previous …

Non-orthogonal multiple access (NOMA) has become the key technology in the future 5G
wireless networks. It can achieve multi-user multiplexing in the transmit power domain by …

Sparse code multiple access (SCMA) and power-domain nonorthogonal multiple access
(PDNOMA) have been considered for use with fifth-generation (5G) and beyond mobile …

Prior works either considered outage capacity of wireless video transmission systems but
did not consider NOMA which is a key technology for 5G ultra-reliable low-latency (URLLC) …

This article studies the power-ordered Non-Orthogonal Multiple Access (NOMA) techniques
associated with Low-Density Parity-Check (LDPC) codes, adopted for use in the fifth …

To address the problems of network congestion and spectrum resources shortage in multi-
user large-scale scenarios, this paper proposes a twice random access OFDMA-NOMA-RA …

Because of the improved overall system throughput, spectrum efficiency, and user fairness,
non-orthogonal multiple access (NOMA) is the next stage in telecommunication systems …

Eventually, the wireless system is one of the most prominent and effectively overloaded with
enormous amounts of data information due to the rising number of users. To effectively …

In the previous study [1], deep-neural-network-aided physic al/application layer resource
management for NOMA-OFDMA video transmissions was proposed. Meeting the constraints …