Submission Deadline: 31 May 2019
IEEE Access invites manuscript submissions in the area of Artificial Intelligence for Physical-Layer Wireless Communications.
Artificial Intelligence (AI), including Deep Learning (DL) and deep reinforcement learning (DRL) approaches, well known from computer science (CS) disciplines, are beginning to emerge in wireless communications. These AI approaches were first widely applied to the upper layers of wireless communication systems for various purposes, such as routing establishment/optimization, and deployment of cognitive radio and communication network. These system models and algorithms designed with DL technology greatly improve the performance of communication systems based on traditional methods.
New features of future communications, such as complex scenarios with unknown channel models, high speed and accurate processing requirements, make traditional methods no longer suitable, and provides many more potential applications of DL. DL technology has become a new hotspot in the research of physical-layer wireless communications and challenges conventional communication theories. Currently, DL-based ‘black-box’ methods show promising performance improvements but have certain limitations, such as the lack of solid analytical tools and the use of architectures specifically designed for communication and implementation research. With the development of DL technology, in addition to the traditional neural network-based data-driven model, the model-driven deep network model and the DRL model (i.e. DQN) which combined DL with reinforcement learning, are more suitable for dealing with future complex communication systems. As in most cases of wireless resource allocation, there are no definite samples to train the model, hence DRL, which trains the model by maximizing the reward associated with different actions, can be adopted.
This Special Section in IEEE Access focuses on the application of DL/DRL methods to physical-layer wireless communications to make future communications more intelligent. We invite submissions of high-quality original technical and survey articles, which have not been published previously, on DL/DRL techniques and their applications for wireless communication and signal processing.
The topics of interests include, but are not limited to:
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Associate Editor: Guan Gui, Nanjing University of Posts and Telecommunications, China
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IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland
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