… activities in machine learning and wireless systems. … deep reinforcement learning approach
to wireless networks to … 1, we introduce machine learning algorithms, which are classified …

… Advanced technologies are required in future mobile wireless networks to support services
with … Deep Learning (DL), one of the most exciting developments in machine learning and big …

… This article is concerned with machine learning-based techniques that exploit radio frequency
(RF) spectrum information to classify wireless devices. Although the study of the wireless …

… to facilitate the application of deep learning to wireless network design. To this end, two
main methods for embedding expert knowledge into deep-learning techniques are discussed, …

… His research interests include resource allocation in wireless networks, machine learning,
adversarial learning, and security. He is the coauthor of the IEEE HST 2018 Best Paper Award…

… the learning processing for the decoder. Compared to other machine learning approaches,
… (MMSE) equalizer, the proposed adaptive deep learning (ADL) based AE demonstrates a …

… mitigation strategies to continue effective use of the scarce spectral resources and enable
the coexistence of heterogeneous wireless networks. In this paper, we investigate end-to-end …

… growth of the data demand in the wireless networks driven by the development of new … GB
per capita by 2021, with the fraction of wireless and mobile devices of more than 63 percent. In …

… with their environment and learn from their mistakes. Additionally, we also prove that the
proposed multi-agent Q-learning based trajectory design and power control algorithm can …

… unfolded approaches reviewed in this article are positioned explicitly in the context of the
requirements imposed by the next generation of cellular networks. Finally, this article motivates …