Signal Processing and Wireless Communications PhD Projects at TMU

Project Overview

This PhD project focuses on advanced research in signal processing and wireless communications, including areas such as federated learning in wireless networks, network coding techniques, and resilient communication technologies for UAV and IoT networks. The aim is to develop new methods for enhancing energy efficiency, throughput, and connectivity in next-generation communication systems.

What You Will Do

You will investigate and develop novel algorithms for resource allocation, decentralized aggregation, and network coding in complex wireless environments. The projects may involve studies on NOMA-enabled IoT systems, relay-assisted networks, fog and cloud radio access networks, and reconfigurable intelligent surface (RIS)-assisted UAV networks.

Expected Outcomes

The research will lead to innovative energy-efficient communication protocols and improved wireless network performance. Outcomes include scalable federated learning frameworks, enhanced content delivery strategies using reinforcement learning, and optimized deployment of RIS technology to improve UAV network connectivity.

Why This Matters

Addressing the challenges of energy consumption, bandwidth efficiency, and connectivity in wireless communication networks is critical for the continued expansion of IoT and smart city technologies. This research delivers practical solutions for sustainable, resilient wireless infrastructures supporting emerging applications in autonomous vehicles, edge computing, and real-time data analytics.