Accurate perceptual knowledge of atmospheric characteristics in the propagation path is of
great significance for the design of communication systems. However, the atmosphere …

The end-to-end autoencoder is a novel and attracting concept to innovate communication
system architecture. In its training stage, the end-to-end autoencoder needs differentiable …

This paper models an end-to-end communications system for the NextG radio access
network (RAN) as an autoencoder (AE) subject to interference effects. The transmitter …

In this chapter, we discuss the artificial intelligence-enhanced multiple access. Section 6.1
introduces the motivation of applying deep multi-task learning to end-to-end optimization of …

5G large-scale commercial enterprises will provide high-speed and low-latency
communication services, but it also challenges optimization of system. In particular, the …

This article presents a differential detection scheme for the uplink of a massive MIMO system
that employs one-bit quantizers on each receive antenna. We focus on the detection of …

The signals detections in MIMOs system under different noise channels is major challenges
for researchers in this time. Hence, in this paper the deep learning (DL) techniques was …

As an important part of AI, deep learning is widely used in image classification and speech
recognition. In particular, the application of deep neural networks with powerful digital signal …

This paper investigates the secrecy parameter of the Multiple Input Single Output (MISO)
system based on Unsupervised Deep Learning using an autoencoder fitted with a single …

Abstract Selina Shrestha,“Machine Learning Based Spatial Modulation for IoT Networks”, M.
Sc. Thesis, M. Sc. in Electrical and Computer Engineering, Department of Electrical …