Deep-learning-enhanced NOMA transceiver design for massive MTC: Challenges, state of the art, and future directions
Non-orthogonal multiple access (NOMA) is a promising evolution path to meet the
requirements of massive machine type communications (mMTC) in 5G and beyond …
requirements of massive machine type communications (mMTC) in 5G and beyond …
ViterbiNet: A deep learning based Viterbi algorithm for symbol detection
Symbol detection plays an important role in the implementation of digital receivers. In this
work, we propose ViterbiNet, which is a data-driven symbol detector that does not require …
work, we propose ViterbiNet, which is a data-driven symbol detector that does not require …
[PDF][PDF] Statistical tools and methodologies for urllc-a tutorial
Ultra-reliable low-latency communication (URLLC) constitutes a key service class of the fifth
generation and beyond cellular networks. Notably, designing and supporting URLLC poses …
generation and beyond cellular networks. Notably, designing and supporting URLLC poses …
Learning to demodulate from few pilots via offline and online meta-learning
This paper considers an Internet-of-Things (IoT) scenario in which devices sporadically
transmit short packets with few pilot symbols over a fading channel. Devices are …
transmit short packets with few pilot symbols over a fading channel. Devices are …
Meta learning-based MIMO detectors: Design, simulation, and experimental test
Deep neural networks (NNs) have exhibited considerable potential for efficiently balancing
the performance and complexity of multiple-input and multiple-output (MIMO) detectors …
the performance and complexity of multiple-input and multiple-output (MIMO) detectors …
Generative-adversarial-network enabled signal detection for communication systems with unknown channel models
L Sun, Y Wang, AL Swindlehurst… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
The Viterbi algorithm is widely adopted in digital communication systems because of its
capability of realizing maximum-likelihood signal sequence detection. However …
capability of realizing maximum-likelihood signal sequence detection. However …
A note on implementation methodologies of deep learning-based signal detection for conventional MIMO transmitters
J Xia, D Deng, D Fan - IEEE Transactions on Broadcasting, 2020 - ieeexplore.ieee.org
Baek et al. proposed a deep learning-based signal detector for conventional MIMO systems,
which is a pioneering work of applying artificial intelligence into wireless communications …
which is a pioneering work of applying artificial intelligence into wireless communications …
End-to-end fast training of communication links without a channel model via online meta-learning
When a channel model is not available, the end-to-end training of encoder and decoder on
a fading noisy channel generally requires the repeated use of the channel and of a feedback …
a fading noisy channel generally requires the repeated use of the channel and of a feedback …
Enhanced few-shot learning for intrusion detection in railway video surveillance
Video surveillance is gaining increasing popularity to assist in railway intrusion detection in
recent years. However, efficient and accurate intrusion detection remains a challenging …
recent years. However, efficient and accurate intrusion detection remains a challenging …
Online supervised learning for traffic load prediction in framed-ALOHA networks
Predicting the current backlog, or traffic load, in framed-ALOHA networks enables the
optimization of resource allocation, eg, of the frame size. However, this prediction is made …
optimization of resource allocation, eg, of the frame size. However, this prediction is made …