Global Navigation Satellite Systems (GNSS) are essential for billions of devices, providing free global access and precise positioning. However, GNSS receivers are high-energy consumers, which complicates their use in energy-limited IoT platforms like asset or wildlife tracking.
M.E. Antoine Grenier's dissertation explores the application of approximate computing (AxC) to GNSS processing. The research offers a novel approach to reducing energy consumption in GNSS receivers.
“AxC reduces energy consumption by trading off computational accuracy while still meeting application requirements. The research demonstrates that AxC can significantly improve the energy efficiency of GNSS receivers, making them more suitable for IoT applications,” Grenier says.
The study supports the development of sustainable solution for IoT apps
The development of the SyDR benchmarking framework is an important outcome of Grenier’s work. SyDR helps identify optimization opportunities in GNSS processing, enabling further refinement of algorithms. This framework is a valuable tool for researchers and engineers in the field, and it is available in open-source on Github.
A key aspect of Grenier's work is the use of inexact arithmetic in GNSS receiver processing, particularly in correlation operations. Inexact arithmetic can result in substantial energy savings with limited impact on computation accuracy.
“The experiments showed successful acquisition and tracking of GNSS signals using an inexact multiplier unit, which can achieve huge energy saving depending on the unit, e.g. up to 87 % energy saved in multiplication operations based on the multipliers used in the study,” he says.
By leveraging approximate computing, the work supports the development of sustainable and energy-efficient satellite positioning solution for IoT applications.
Public defence on Friday 21 February
The doctoral dissertation of M.E. Antoine Grenier in the field of electrical engineering titled Approximating Techniques for Low-Power GNSS Receivers will be publicly examined at the Faculty of Information Technology and Communication Sciences at Tampere University on Friday, 21 February 2025 at 12.00 at Hervanta campus, Tietotalo, in the TB109 auditorium (address: Korkeakoulunkatu 1, 33720 Tampere).
The opponent will be Professor Emeritus Terry Moore from the University of Nottingham. The custos will be Professor Jari Nurmi from Tampere University. The work has been co-supervised by Professor Simona Lohan from Tampere University, and D.Sc. (Tech.) Aleksandr Ometov from Tampere University.
The doctoral dissertation is available online.
The public defence can be followed via remote connection.