Edge-Native Environmental Sensing through SDR and TinyML-MEC Framework
This PhD opportunity at Aston University focuses on pioneering edge-native environmental sensing by integrating Software-Defined Radio (SDR), TinyML, and Mobile Edge Computing (MEC) into a novel sensing-communication framework. The project aims to enable autonomous adaptiveness to radio frequency (RF) fragility and uncertainties, a critical challenge as wireless networks evolve toward 6G and expand into higher frequency bands susceptible to environmental changes.
Within the context of Integrated Sensing and Communications (ISAC), the research will transform communication networks from passive data conduits into cognitive infrastructures capable of perceiving their physical surroundings. This shift supports advanced applications such as urban digital twins and autonomous vehicular navigation. The project’s primary technical challenges include extracting environmental monitoring information using lightweight, distributed AI, and designing hybrid AI architectures that intelligently partition and offload complex computational tasks onto hardware-constrained platforms.
The core objective is to compress deep learning processes for environmental awareness into ultra-lightweight TinyML modules deployable directly on SDRs. These modules, seamlessly integrated with MEC, will enable rapid, low-latency environmental sensing, facilitating next-generation wireless communication paradigms. Candidates will address bottlenecks such as efficient acquisition and processing of high-dimensional environmental sensing data, architecting hybrid modules for high-granularity sensing tasks (e.g., user tracking, dynamic obstacle recognition, predictive channel estimation), and robustly decoupling task-specific physical signatures from entangled wireless metrics like Channel State Information (CSI) amidst severe multipath fading and environmental noise.
Applicants should have a First or Upper Second Class undergraduate degree in a relevant subject, or a First or Upper Second Class undergraduate degree and a Merit or Distinction in a Masters degree. Overseas qualifications are considered if equivalent. Preferred skills include expertise in SDR, embedded systems, FPGA development, and deployable AI. Industrial experience is highly valued. English language requirements must be met, and all supporting documents must be submitted for the application to be considered.
The project covers all tuition fees and offers a 20-hour weekly part-time associate position. However, candidates are responsible for costs related to relocation, visa, flights, and NHS Surcharge. The position is based at Aston Campus in Birmingham, UK, and regular in-person visits are expected. Interviews will be conducted online via Microsoft Teams.
For enquiries, contact Dr. Zhengjia Xu ([email protected]) or Prof. Jose Maria Alcaraz Calero ([email protected]). For application process questions, contact the Postgraduate Admissions team ([email protected]). Apply via the provided link and ensure all required documents are included. Incomplete applications will be automatically rejected.
