Signal processing intern

Description About Ceva Ceva is at the forefront of the Smart Edge revolution, with innovative state-of-the-art Silicon and Software solutions that enable products to Connect, Sense and Infer. Within the Wireless Internet of Things (WIoT) Business Unit, we are offering you a unique opportunity to shape the future of connected devices. Our advanced wireless technologies, including Bluetooth, Wi-Fi UWB, and 5G Cellular IoT, are integrated into over a Billion devices annually, driving innovation across industries. About the job Version 6 of the Bluetooth standard introduces a major innovation: Channel Sounding, a technology that enables distance estimation between devices through the analysis of the phase of exchanged radio signals (PBR – Phase-Based Ranging). This feature opens the door to innovative applications in indoor positioning, asset tracking, digital key and contextual interaction. It relies on advanced signal processing algorithms. The objective of this internship is to perform a comparative study of existing distance estimation algorithms in order to evaluate their accuracy, robustness, and complexity. In particular, the potential of neural network-based approaches (AI) will be assessed. The internship will take place within the Signal Processing Team, a multidisciplinary group responsible for the algorithms used in our connectivity IPs. You will be supervised by experienced engineers in a stimulating and collaborative environment. In practical terms, the internship will be organized into several phases: Familiarization with Ceva/RivieraWaves' current developments. State-of-the-art review of phase-based distance estimation methods. Setup of a comparative testing environment. Comparative evaluation of selected algorithms based on their potential effectiveness (performance/complexity trade-off). Requirements • Final-year engineering school or Master's degree student. • Specialized in, or knowledgeable about, signal processing. • Prior experience with MATLAB. • Curious, rigorous, and equipped with strong analytical skills. • Duration: 6 months • Start date: Early 2027