On removing routing protocol from future wireless networks: A real-time deep learning approach for intelligent traffic control
Recently, deep learning has appeared as a breakthrough machine learning technique for
various areas in computer science as well as other disciplines. However, the application of …
various areas in computer science as well as other disciplines. However, the application of …
Behavioral modeling and linearization of wideband RF power amplifiers using BiLSTM networks for 5G wireless systems
Characterization and linearization of RF power amplifiers (PAs) are key issues of fifth-
generation wireless communication systems, especially when high peak-to-average ratio …
generation wireless communication systems, especially when high peak-to-average ratio …
Unsupervised learning-based fast beamforming design for downlink MIMO
In the downlink transmission scenario, power allocation and beamforming design at the
transmitter are essential when using multiple antenna arrays. This paper considers a …
transmitter are essential when using multiple antenna arrays. This paper considers a …
Intelligent routing based on reinforcement learning for software-defined networking
DM Casas-Velasco, OMC Rendon… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Traditional routing protocols employ limited information to make routing decisions, which
can lead to a slow adaptation to traffic variability, as well as restricted support to the Quality …
can lead to a slow adaptation to traffic variability, as well as restricted support to the Quality …
Blockchain and AI technology convergence: Applications in transportation systems
The blockchain and artificial intelligence (AI) have been the focal point of innovations and
received increasing attention of the community over the last years. The blockchain …
received increasing attention of the community over the last years. The blockchain …
Enabling collaborative edge computing for software defined vehicular networks
Edge computing has great potential to address the challenges in mobile vehicular networks
by transferring partial storage and computing functions to network edges. However, it is still …
by transferring partial storage and computing functions to network edges. However, it is still …
Space-air-ground integrated multi-domain network resource orchestration based on virtual network architecture: A DRL method
Traditional ground wireless communication networks cannot provide high-quality services
for artificial intelligence (AI) applications such as intelligent transportation systems (ITS) due …
for artificial intelligence (AI) applications such as intelligent transportation systems (ITS) due …
ThriftyEdge: Resource-efficient edge computing for intelligent IoT applications
In this article we propose a new paradigm of resource-efficient edge computing for the
emerging intelligent IoT applications such as flying ad hoc networks for precision agriculture …
emerging intelligent IoT applications such as flying ad hoc networks for precision agriculture …
Leveraging deep reinforcement learning for traffic engineering: A survey
After decades of unprecedented development, modern networks have evolved far beyond
expectations in terms of scale and complexity. In many cases, traditional traffic engineering …
expectations in terms of scale and complexity. In many cases, traditional traffic engineering …
Threats of adversarial attacks in DNN-based modulation recognition
With the emergence of the information age, mobile data has become more random,
heterogeneous and massive. Thanks to its many advantages, deep learning is increasingly …
heterogeneous and massive. Thanks to its many advantages, deep learning is increasingly …