ACO-based Scheme in Edge Learning NOMA Networks for Task-Oriented Communications
Conventional communications systems centered on data prioritize maximizing network
throughput using Shannon's theory, which is primarily concerned with securely transmitting …
throughput using Shannon's theory, which is primarily concerned with securely transmitting …
Fast-grant learning-based approach for machine-type communications with NOMA
M El Tanab, W Hamouda - ICC 2021-IEEE International …, 2021 - ieeexplore.ieee.org
In this paper, we propose a non-orthogonal multiple access (NOMA)-based communication
framework that allows machine-type devices (MTDs) to access the network while avoiding …
framework that allows machine-type devices (MTDs) to access the network while avoiding …
Deep multi-agent reinforcement learning for resource allocation in NOMA-enabled MEC
Non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are being
considered as promising technologies to address the stringent demands of the emerging …
considered as promising technologies to address the stringent demands of the emerging …
Deep multi-task learning for cooperative NOMA: System design and principles
Envisioned as a promising component of the future wireless Internet-of-Things (IoT)
networks, the non-orthogonal multiple access (NOMA) technique can support massive …
networks, the non-orthogonal multiple access (NOMA) technique can support massive …
Resource allocation and device pairing for energy-efficient NOMA-enabled federated edge learning
In the era of Fifth Generation of cellular networks (5G), Internet of Things (IoT) devices are
becoming much more popular and accumulate a lot of data. With the advantages of privacy …
becoming much more popular and accumulate a lot of data. With the advantages of privacy …
Meta-learning for RIS-assisted NOMA Networks
A novel reconfigurable intelligent surfaces (RISs)-based transmission framework is
proposed for downlink non-orthogonal multiple access (NOMA) networks. We propose a …
proposed for downlink non-orthogonal multiple access (NOMA) networks. We propose a …
Transmit power pool design for grant-free NOMA-IoT networks via deep reinforcement learning
Grant-free non-orthogonal multiple access (GF-NOMA) is a potential multiple access
framework for short-packet internet-of-things (IoT) networks to enhance connectivity …
framework for short-packet internet-of-things (IoT) networks to enhance connectivity …
Distributed auto-learning gnn for multi-cell cluster-free NOMA communications
A multi-cell cluster-free NOMA framework is proposed, where both intra-cell and inter-cell
interference are jointly mitigated via flexible cluster-free successive interference cancellation …
interference are jointly mitigated via flexible cluster-free successive interference cancellation …
DeepNOMA: A unified framework for NOMA using deep multi-task learning
Non-orthogonal multiple access (NOMA) will provide massive connectivity for future Internet
of Things. However, the intrinsic non-orthogonality in NOMA makes it non-trivial to approach …
of Things. However, the intrinsic non-orthogonality in NOMA makes it non-trivial to approach …
Capacity-driven end-to-end learning approach for NOMA with finite-alphabet inputs
J Fan, Z Sun, G Yue, J Yu - Physical Communication, 2023 - Elsevier
Optimal Non-orthogonal multiple access (NOMA) design with practical finite-alphabet inputs
instead of ideal Gaussian inputs has been addressed in this paper. With the aid of tight …
instead of ideal Gaussian inputs has been addressed in this paper. With the aid of tight …