The last years have seen an unprecedented interest in the utilization of aerial platforms not
only to support applications (eg monitoring) but also to assist in relaying signals from …

This paper explores an orthogonal time frequency space (OTFS)-assisted integrated
sensing and communication (ISAC) system in vehicular networks. We present a deep …

Nowadays, the integration of conventional 5G communication systems and artificial
intelligence (AI) has become one of the important trends for the evolution of future advanced …

Access to reliable estimates of the wireless channel, such as the channel state information
(CSI) and the received signal strength would open opportunities for timely adaptation of …

We believe most communications can eventually be available through wireless services.
The move toward „wireless everything “is being driven by users, producers of information …

This paper studies the applications of Deep Learning (branch of Machine Learning) in 5G
wireless communication systems. Deep Learning requires having large sets of data for …

In this paper, we present a two‐stage scalable channel estimator (TSCE), a deep learning
(DL)‐based scalable, and robust channel estimator for wireless cellular networks, which is …

Accurately modeling and predicting wireless channel quality variations is essential for a
number of networking applications such as scheduling and improved video streaming over …

In this paper, we analyze the performance of link-level abstraction for orthogonal frequency-
division multiplexing (OFDM) and single-carrier (SC) modes in IEEE 802.11 ay wireless …

In this paper, we propose a novel deep learning based channel estimation scheme for IEEE
802.11 p vehicle-to-everything (V2X) communication systems. A major challenge in the V2X …