The existing end-to-end (E2E) wireless communication systems require fewer
communication modules and have a simple processing signal flow, compared to …

Abstract Improving Machine-to-Machine (M2M) communication is essential for the
development of Smart Factory as data can be exchanged and processed more efficiently …

In this paper, a stacked autoencoder network is utilised to realise the signal constellation
and transceivers adapted to the dimmable indoor visible light communication system in …

Thesis Title Page 1 Deep Learning Techniques for Next Generation Wireless Networks A thesis
submitted to The University of Manchester for the degree of Doctor of Philosophy in the Faculty …

The traditional communication model based on chain of multiple independent processing
blocks is constraint to efficiency and introduces artificial barriers. Thus, each individually …

The resurgence of deep learning techniques has brought forth fundamental changes to how
hard problems could be solved. It used to be held that the solutions to complex wireless …

Wireless communication is a widely used technology for transmitting information over long
distances without the use of physical connections. Various environmental factors make …

The ever–growing data traffic demand has been driving the optical networks to constantly
evolve over the years. To efficiently meet this demand, the future optical communication …

Channel selection plays an essential role in uninterrupted and efficient cognitive
communication. A secondary user applies a comparative sensing approach in different time …

In this paper, we consider deep unfolding the standard iterative conjugate gradient (CG)
algorithm to solve a linear system of equations. Instead of being adjusted with known rules …