The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of
intelligent networks with the provision of some isolated artificial intelligence (AI) operations …

The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …

Signal processing, communications, and control have traditionally relied on classical
statistical modeling techniques. Such model-based methods utilize mathematical …

This paper deals with the use of emerging deep learning techniques in future wireless
communication networks. It will be shown that the data-driven approaches should not …

This paper investigates task-oriented communication for edge inference, where a low-end
edge device transmits the extracted feature vector of a local data sample to a powerful edge …

Intelligent communication is gradually becoming a mainstream direction. As a major branch
of machine learning, deep learning (DL) has been applied in physical layer communications …

Mathematical optimization is now widely regarded as an indispensable modeling and
solution tool for the design of wireless communications systems. While optimization has …

In this paper, we consider the use of deep neural networks in the context of Multiple-Input-
Multiple-Output (MIMO) detection. We give a brief introduction to deep learning and propose …

It has been a long-held belief that judicious resource allocation is critical to mitigating
interference, improving network efficiency, and ultimately optimizing wireless communication …

Beamforming is an effective means to improve the quality of the received signals in multiuser
multiple-input-single-output (MISO) systems. Traditionally, finding the optimal beamforming …