A survey on machine learning techniques for massive MIMO configurations: Application areas, performance limitations and future challenges
PK Gkonis - IEEE Access, 2022 - ieeexplore.ieee.org
The deployment of fifth-generation (5G) broadband wireless cellular networks has enabled
the support of highly demanding applications, paving the way towards global broadband …
the support of highly demanding applications, paving the way towards global broadband …
The road to 6G: a comprehensive survey of deep learning applications in cell-free massive MIMO communications systems
The fifth generation (5G) of telecommunications networks is currently commercially
deployed. One of their core enabling technologies is cellular Massive Multiple-Input-Multiple …
deployed. One of their core enabling technologies is cellular Massive Multiple-Input-Multiple …
Resource allocation for cell-free massive MIMO-enabled URLLC downlink systems
Ultra-Reliable and low-latency communication (URLLC) is a pivotal technique for enabling
the wireless control over industrial Internet-of-Things (IIoT) devices. By deploying distributed …
the wireless control over industrial Internet-of-Things (IIoT) devices. By deploying distributed …
Exploring the impact of power control strategies for enhanced IoT connectivity in massive MIMO
BM Lee - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
The use of massive multiple-input–multiple-output (MIMO) technology is gaining traction as
a potential solution to various wireless challenges, particularly in addressing the deployment …
a potential solution to various wireless challenges, particularly in addressing the deployment …
Cell-free networking for integrated data and energy transfer: Digital twin based double parameterized dqn for energy sustainability
Cell-free networking enables full cooperation among distributed access points (APs). This
paper focuses on reducing the long-term energy consumption of a cell-free network in the …
paper focuses on reducing the long-term energy consumption of a cell-free network in the …
Heterogeneous graph neural network for power allocation in multicarrier-division duplex cell-free massive MIMO systems
In order to maximize the spectral efficiency (SE) in multicarrier-division duplex (MDD)
enabled cell-free massive MIMO (CF-mMIMO), a heterogeneous graph neural network …
enabled cell-free massive MIMO (CF-mMIMO), a heterogeneous graph neural network …
Access point clustering in cell-free massive MIMO using conventional and federated multi-agent reinforcement learning
B Banerjee, RC Elliott, WA Krzymieñ… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Cell-free massive multiple-input multiple-output (MIMO) systems consist of geographically-
distributed multi-antenna access points (APs) that form a virtual massive MIMO array. To …
distributed multi-antenna access points (APs) that form a virtual massive MIMO array. To …
A GNN approach for cell-free massive MIMO
Beyond 5G wireless technology Cell-Free Massive MIMO (CFmMIMO) downlink relies on
carefully designed pre-coders and power control to attain uniformly high rate coverage …
carefully designed pre-coders and power control to attain uniformly high rate coverage …
Defending adversarial attacks on deep learning-based power allocation in massive MIMO using denoising autoencoders
Recent work has advocated for the use of deep learning to perform power allocation in the
downlink of massive MIMO (maMIMO) networks. Yet, such deep learning models are …
downlink of massive MIMO (maMIMO) networks. Yet, such deep learning models are …
Power allocation in ultra-dense networks through deep deterministic policy gradient
J Liu, H Zhang - IEEE Wireless Communications Letters, 2022 - ieeexplore.ieee.org
The existing reinforcement learning-based downlink power allocation (PA) schemes mostly
consider the power optimization space as a discrete value space, however, their results will …
consider the power optimization space as a discrete value space, however, their results will …