Deep learning-based blind multiple user detection for grant-free scma and musa systems
Massive machine-type communications (mMTC) in 6G requires supporting a massive
number of devices with limited resources, posing challenges in efficient random access …
number of devices with limited resources, posing challenges in efficient random access …
Deep learning-based blind multiple user detection for grant-free SCMA and MUSA systems
Massive machine-type communications (mMTC) in 6G requires supporting a massive
number of devices with limited resources, posing challenges in efficient random access …
number of devices with limited resources, posing challenges in efficient random access …
Active user detection and channel estimation for massive machine-type communication: Deep learning approach
Recently, massive machine-type communications (mMTCs) have become one of key use
cases for 5G. In order to support massive users transmitting small data packets at low rates …
cases for 5G. In order to support massive users transmitting small data packets at low rates …
Enumeration and identification of active users for grant-free NOMA using deep neural networks
In next-generation mobile radio systems, multiple access schemes will support a massive
number of uncoordinated devices exhibiting sporadic traffic, transmitting short packets to a …
number of uncoordinated devices exhibiting sporadic traffic, transmitting short packets to a …
DeepMuD: Multi-user detection for uplink grant-free NOMA IoT networks via deep learning
In this letter, we propose a deep learning-aided multi-user detection (DeepMuD) in uplink
non-orthogonal multiple access (NOMA) to empower the massive machine-type …
non-orthogonal multiple access (NOMA) to empower the massive machine-type …
Structured Sparse Bayesian Learning Based Multiuser Detectors for Uplink Grant-Free NOMA With Variable User Activities
In this work, we study the grant-free non-orthogonal multiple access (GF-NOMA) system to
support the massive machine-type communications (mMTC), where the number of users is …
support the massive machine-type communications (mMTC), where the number of users is …
Bayesian learning-based multiuser detection for grant-free NOMA systems
X Zhang, P Fan, J Liu, L Hao - IEEE Transactions on Wireless …, 2022 - ieeexplore.ieee.org
Grant-Free Non-Orthogonal Multiple Access (GF-NOMA) is considered as a promising
technology to support the massive connectivity of Machine-Type Communications (MTC) …
technology to support the massive connectivity of Machine-Type Communications (MTC) …
Prior information aided deep learning method for grant-free NOMA in mMTC
In massive machine-type communications (mMTC), the conflict between millions of potential
access devices and limited channel freedom leads to a sharp decrease in spectrum …
access devices and limited channel freedom leads to a sharp decrease in spectrum …
An efficient message passing algorithm for active user detection and channel estimation in NOMA
W Dai, H Wei, J Zhou, W Zhou - 2019 IEEE 90th Vehicular …, 2019 - ieeexplore.ieee.org
In 5G wireless communication network, massive machine type communication (mMTC) is an
emerging research topic. For mMTC, non-orthogonal multiple access (NOMA) has been …
emerging research topic. For mMTC, non-orthogonal multiple access (NOMA) has been …
Deep neural network-based joint active user detection and channel estimation for mMTC
As a means to support the access of massive machine-type communication devices, grant-
free access and nonorthogonal multiple access (NOMA) have received a lot of attention …
free access and nonorthogonal multiple access (NOMA) have received a lot of attention …