Ambient backscatter Communications for IoT

Summary

This project investigates ambient backscatter communications as a low-power and cost-effective solution for the Internet of Things (IoT), enabling battery-free devices to communicate by harvesting and reflecting existing radio signals. It offers opportunities to develop innovative system designs and protocols that enhance connectivity, energy efficiency, and scalability for massive IoT deployments

Supervisor

Dr Zihuai Lin.

Research location

Electrical and Computer Engineering

Synopsis

This research focuses on ambient backscatter communications (AmBC) as a promising paradigm for sustainable Internet of Things (IoT) connectivity. Unlike conventional radios, AmBC devices do not generate their own carrier signals but instead harvest and modulate existing RF signals (e.g., WiFi, TV, or cellular transmissions), enabling ultra-low-power and battery-free communications. The project aims to investigate system models, modulation and coding schemes, and interference management strategies to overcome challenges such as low data rates, limited range, and co-channel interference. Advanced techniques such as machine learning-assisted signal detection, multiple access design, and cooperative networking will be explored to enhance the reliability and scalability of AmBC systems. By addressing these challenges, the research will contribute to the development of energy-efficient, cost-effective, and sustainable IoT networks, supporting applications in smart cities, healthcare, and industrial automation.

Research Techniques / Methodologies / Technologies

The project will combine theoretical modelling, algorithm development, and experimental validation. Research techniques include signal processing, coding and modulation design, optimisation, and machine learning methods for reliable backscatter detection. Tools such as MATLAB, Python, and hardware testbeds with software-defined radios (SDR) may be employed to simulate and prototype ambient backscatter systems in real-world IoT scenarios.

Offering

A scholarship for 3.5 years at the RTP stipend rate (currently $41,753 in 2025). International applicants will have their tuition fees covered.

Successful candidates:

must have a strong background in wireless communications, digital signal processing, and applied mathematics.
must have a Experience with IoT systems, RF hardware, or machine learning for communications is desirable.
should have proficiency in programming languages such as MATLAB, Python, or C/C++, along with an interest in next-generation IoT technologies and energy-efficient communications,

How to apply:

To apply, please email [email protected] the following:

a detailed CV, including academic qualifications, research experience and publications
academic transcripts

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Opportunity ID

The opportunity ID for this research opportunity is 3692