Communications

An applied working environment that aims to link the theoretical concepts of communication systems and signal processing with smart practical applications

Vision

Leadership in academic and research excellence in the simulation and development of smart communication systems, and building an integrated virtual environment that enables students to devise artificial intelligence software solutions to address the challenges of next-generation networks.

Mission

To provide high-quality applied education that links the theoretical concepts of communications with software modelling using MATLAB and Simulink, and to train students to employ machine learning and deep learning algorithms to analyse signals and improve the efficiency of data transmission, qualifying them for the engineering labour market and scientific research

Objectives

Programming proficiency: equipping students with the skills to write code and design simulation blocks (Simulink) to fully model digital transmitter and receiver systems.

Digital analysis: training students to examine and analyse signals in the time and frequency domains, and to design digital filters to remove noise.

Smart application: integrating MATLAB's artificial intelligence tools (such as the Deep Learning Toolbox) to predict network faults, tune smart antennas and optimise frequency allocation.

Quantitative evaluation: giving students the ability to compute key performance indicators in software, such as the bit error rate (BER) and the signal-to-noise ratio (SNR)

. Supporting innovation: providing a flexible environment for simulating graduation projects and advanced scientific research without the cost of complex physical equipment.