Nonorthogonal multiple access (NOMA) has been considered as an essential multiple
access technique for enhancing system capacity and spectral efficiency in future …

Given the requirements of increased data rate and massive connectivity in the Internet-of-
things (IoT) applications of the fifth-generation communication systems (5G), non-orthogonal …

Presently, Non-Orthogonal Multiple Access (NOMA) frequently uses Successive Interference
Cancellation (SIC) with channel estimation to detect the receivers' signal successfully …

In this letter, we propose a novel deep learning based approach for joint channel estimation
and signal detection in orthogonal frequency division multiplexing (OFDM) systems by …

Grant-free non-orthogonal multiple access is an emerging research topic in machine-type
communications, which is used to reduce signaling overhead. In this context, this letter …

This paper introduces a novel deep learning (DL) based successive interference
cancellation (SIC) scheme for an uplink multiple-input multiple-output non-orthogonal …

For massive machine-type communications, centralized control may incur a prohibitively
high overhead. Grant-free non-orthogonal multiple access (NOMA) provides possible …

Channel estimation is very challenging for multiple-input and multiple-output orthogonal
frequency division multiplexing (MIMO-OFDM) systems in high mobility environments with …

In this paper, a deep learning-based successive interference cancellation (SIC) scheme for
use in nonorthogonal multiple access (NOMA) communication systems is investigated …

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) …