Blind goal-oriented massive access for future wireless networks
S Daei, M Kountouris - IEEE Transactions on Signal Processing, 2023 - ieeexplore.ieee.org
Emerging communication networks are envisioned to support massive wireless connectivity
of heterogeneous devices with sporadic traffic and diverse requirements in terms of latency …
of heterogeneous devices with sporadic traffic and diverse requirements in terms of latency …
[HTML][HTML] Spectral Efficiency Improvement Using Bi-Deep Learning Model for IRS-Assisted MU-MISO Communication System
The intelligent reflecting surface (IRS) is a two-dimensional (2D) surface with a
programmable structure and is composed of many arrays. The arrays are used to supervise …
programmable structure and is composed of many arrays. The arrays are used to supervise …
Intelligent near-field channel estimation for terahertz ultra-massive MIMO systems
The terahertz (THz) communication systems as-sisted by ultra-massive (UM) number of
antennas have been considered as a promising solution for future 6G wireless …
antennas have been considered as a promising solution for future 6G wireless …
Efficient Channel prediction technique using AMC and deep learning algorithm for 5G (NR) mMTC devices
Efficient utilisation of adaptive modulation and coding ensures the quality transmission of
information bits through the significant reduction in bit error rate (BER). Channel prediction …
information bits through the significant reduction in bit error rate (BER). Channel prediction …
D-TLoc: Deep learning-aided hybrid tdoa/aoa-based localization
Beamforming with the multiple-input-multiple-output (MIMO) antenna arrays has been
exploited to compensate significant signal power attenuation of high frequency wave. For …
exploited to compensate significant signal power attenuation of high frequency wave. For …
Data-aided Active User Detection with a User Activity Extraction Network for Grant-free SCMA Systems
In grant-free sparse code multiple access (GF-SCMA) system, active user detection (AUD) is
a major performance bottleneck as it involves complex combinatorial problem, which makes …
a major performance bottleneck as it involves complex combinatorial problem, which makes …
Deep Learning-aided Parametric Sparse Channel Estimation for Terahertz Massive MIMO Systems
Terahertz (THz) communications is considered as one of key solutions to support extremely
high data demand in 6G. One main difficulty of the THz communication is the severe signal …
high data demand in 6G. One main difficulty of the THz communication is the severe signal …
Deep Learning Based Pilot-Free Transmission: Error Correction Coding for Low-Resolution Reception Under Time-Varying Channels
Recently, deep learning aided methods have been developed for error correction coding
with quantitative constraints. However, previous studies only focus on additive white …
with quantitative constraints. However, previous studies only focus on additive white …
On the Performance of Deep Learning-based Data-aided Active User Detection for GF-SCMA System
The recent works on a deep learning (DL)-based joint design of preamble set for the
transmitters and data-aided active user detection (AUD) in the receiver has demonstrated a …
transmitters and data-aided active user detection (AUD) in the receiver has demonstrated a …
Deep Learning-Assisted Parallel Interference Cancellation for Grant-Free NOMA in Machine-Type Communication
In this paper, we present a novel approach for joint activity detection (AD), channel
estimation (CE), and data detection (DD) in uplink grant-free non-orthogonal multiple access …
estimation (CE), and data detection (DD) in uplink grant-free non-orthogonal multiple access …