In a previous work (Missaoui et al. in IEEE Wirel Commun Lett 6 (2): 150–153, 2017), we
introduced a blind identification method of active users in multi-user MIMO systems …

After about forty years of leap forward, the mobile communications have greatly reshaped
people's life and promoted the development of our society. With the official …

In this paper, we propose a new type of deep learning (DL)-based localization for the urban
NLoS scenarios, termed Intelligent Localization via Spatial Information Embedding (I …

The massive machine-to-machine communication (mM2M) has led to several research
challenges in 5G cellular Internet-of-Things (IoT). Here, radio access network congestion is …

This letter proposes a deep learning-based data-aided active user detection network (D-
AUDN) for grant-free sparse code multiple access (SCMA) systems that leverages both …

With the fast increase in the publicity of the Internet of Things (IoT) and cloud computing, the
requirement for massive connectivity and highly reliable data rates is increasing day by day …

The big success of deep learning (DL) has motivated the application of DL to wireless
systems in recent years. In this paper, we explain issues and corresponding solutions to be …

In recent years, advancements in Artificial Intelligence (AI) have significantly improved
communication systems in terms of data transmission rate, latency, and accuracy, along with …

Introduction: Developing physical level techniques for machine type communications is a
challenging task. In particular developing low complexity channel estimation with acceptable …

The grant-free multiple access technology is regarded as a key enabling technology for
future massive Internet of Things (IoT) sce⁃ nario. In the grant-free access system, the lack …