In this study, we consider the application of deep learning (DL) to tabu search (TS) detection
in large multiple-input multiple-output (MIMO) systems. First, we propose a deep neural …

The Viterbi algorithm is widely adopted in digital communication systems because of its
capability of realizing maximum-likelihood signal sequence detection. However …

In this work, we develop DeepWiPHY, a deep learning-based architecture to replace the
channel estimation, common phase error (CPE) correction, sampling rate offset (SRO) …

Deep learning (DL) based autoencoder (AE) has been proposed recently as a promising,
and potentially disruptive approach to design the physical layer of beyond-5G …

In this letter, we present a downlink pilot design scheme for Deep Learning (DL) based
channel estimation (ChannelNet) in orthogonal frequency-division multiplexing (OFDM) …

Adaptive capacity with cost-efficient resource provisioning is a crucial capability for future 6G
networks. In this work, we conceptualize" expansive networks" which refers to a networking …

Future wireless communications are becoming increasingly complex with different radio
access technologies, transmission backhauls, and network slices, and they play an …

The advent of the wireless communications systems augurs new cutting-edge technologies,
including self-driving vehicles, unmanned aerial systems, autonomous robots, the Internet-of …

In this paper, we introduce a reservoir computing (RC) structure, namely, windowed echo
state network (WESN), for multiple-input-multiple-output orthogonal frequency-division …

Resource allocation has a direct and profound impact on the performance of vehicle-to-
everything (V2X) networks. In this paper, we develop a hybrid architecture consisting of …