This study investigates non-orthogonal multiple access (NOMA) receivers based on deep
learning (DL) employing the long-short term memory technique (LSTM) over frequency-flat …

This paper investigates deep learning (DL) non-orthogonal multiple access (NOMA)
receivers based on long short-term memory (LSTM) under Rayleigh fading channel …

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) …

Non-orthogonal multiple access (NOMA) techniques have drawn much attention for massive
connectivity, heterogeneous data traffic with ultra-low latency requirements, and ultra-high …

This work examines the efficacy of deep learning (DL) based non-orthogonal multiple
access (NOMA) receivers in vehicular communications (VC). Analytical formulations for the …

As a key important approach for next generation communication systems, Non-Orthogonal
Multiple Access (NOMA) has made high attention in the wireless communication. NOMA …

In this paper, the performance of a deep learningbased multiple-input multiple-output
(MIMO) non-orthogonal multiple access (NOMA) system is investigated for 5G radio …

This study investigates the deep learning (DL)-based uplink power domain non-orthogonal
multiple access (PD-NOMA) system, with a focus on channel state information (CSI) …

Non-orthogonal multiple access (NOMA) techniques have the potential to achieve large
connectivity requirements for future-generation wireless communication. NOMA detection …

Non-orthogonal multiple access (NOMA), featuring high spectrum efficiency, massive
connectivity and low latency, holds immense potential to be a novel multi-access technique …