Recent advances in data-driven wireless communication using gaussian processes: a comprehensive survey
Data-driven paradigms are well-known and salient demands of future wireless
communication. Empowered by big data and machine learning techniques, next-generation …
communication. Empowered by big data and machine learning techniques, next-generation …
Rethinking Bayesian learning for data analysis: The art of prior and inference in sparsity-aware modeling
Sparse modeling for signal processing and machine learning, in general, has been at the
focus of scientific research for over two decades. Among others, supervised sparsity-aware …
focus of scientific research for over two decades. Among others, supervised sparsity-aware …
FedLoc: Federated learning framework for data-driven cooperative localization and location data processing
In this overview paper, data-driven learning model-based cooperative localization and
location data processing are considered, in line with the emerging machine learning and big …
location data processing are considered, in line with the emerging machine learning and big …
A review of federated meta-learning and its application in cyberspace security
F Liu, M Li, X Liu, T Xue, J Ren, C Zhang - Electronics, 2023 - mdpi.com
In recent years, significant progress has been made in the application of federated learning
(FL) in various aspects of cyberspace security, such as intrusion detection, privacy …
(FL) in various aspects of cyberspace security, such as intrusion detection, privacy …
Dual attention-based federated learning for wireless traffic prediction
Wireless traffic prediction is essential for cellular networks to realize intelligent network
operations, such as load-aware resource management and predictive control. Existing …
operations, such as load-aware resource management and predictive control. Existing …
A deep learning method based on an attention mechanism for wireless network traffic prediction
M Li, Y Wang, Z Wang, H Zheng - Ad Hoc Networks, 2020 - Elsevier
With the rapid development of wireless networks, the self-management and active
adjustment capabilities of base stations have become crucial. The accurate prediction of …
adjustment capabilities of base stations have become crucial. The accurate prediction of …
A reinforcement learning-based network traffic prediction mechanism in intelligent internet of things
Intelligent Internet of Things (IIoT) is comprised of various wireless and wired networks for
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …
Dynamic VNF placement, resource allocation and traffic routing in 5G
Abstract 5G networks are going to support a variety of vertical services, with a diverse set of
key performance indicators (KPIs), by using enabling technologies such as software-defined …
key performance indicators (KPIs), by using enabling technologies such as software-defined …
From statistical‐to machine learning‐based network traffic prediction
I Lohrasbinasab, A Shahraki… - Transactions on …, 2022 - Wiley Online Library
Nowadays, due to the exponential and continuous expansion of new paradigms such as
Internet of Things (IoT), Internet of Vehicles (IoV) and 6G, the world is witnessing a …
Internet of Things (IoT), Internet of Vehicles (IoV) and 6G, the world is witnessing a …
Scalable learning paradigms for data-driven wireless communication
The marriage of wireless big data and machine learning techniques revolutionizes wireless
systems by introducing data-driven philosophy. However, the ever exploding data volume …
systems by introducing data-driven philosophy. However, the ever exploding data volume …