PhD Project: RF Waveforms for simultaneous applications in radar and communication domains
The closing date for this job submission has passed.
Radio-Frequency (RF) waveforms that can be used simultaneously for applications in the radar and communication domains. The student will be supervised by Dr Francesco Fioranelli and Prof Muhammad Imran at the School of Engineering, University of Glasgow, with the support of Leonardo Airborne and Space Systems.
Frequency spectrum is increasingly becoming an expensive and rare commodity, as we have more and more mobile users and services needing high volume of multimedia data traffic. This creates a “crunching” effect, detrimental for telecommunication applications (cap to the number of users, need for additional infrastructures, increased latency unsuitable for real-time multimedia services), and even more for radar applications (the narrower allocated frequency bandwidth reduces resolution to sense targets of interest, and restricts the possibility of using different parts of the spectrum for different radar tasks, for example detection vs tracking).
This project wants to explore waveform design techniques to enable simultaneous transmission/reception, achieving acceptable performances according to relevant metrics Doppler resolution) applications. At the same time one must ensure that the waveforms can be not only simulated, but also generated with existing RF hardware. These waveforms should be modelled and tested to consider the effect that realistic hardware will have on their performance (a classic example is the impossibility of achieving all the required phase transitions, as these can be simulated but not necessarily generated with actual hardware, in particular medium and high power amplifiers).
Waveforms engineering in this project wants to go beyond frequency diversity (= sharing the same spectrum) and time diversity (= interleaving different waveforms), to exploit forms of coding diversity and orthogonality that can reduce the mutual interference between simultaneous waveforms to acceptable levels. A few ad-hoc solutions have been proposed in the literature, but experimental validation is still a challenging and innovative field, as well as a generalised design approach that can also incorporate the potential of machine learning to select the different parameters. In this regard, the research in wireless communication domain has shown that different waveforms are suitable for different local environments and specific communication needs. Hence it is counterproductive to select only one waveform for all purposes. Machine learning techniques (e.g. reinforcement learning) can enable the self-configuration capability of dual purpose RADAR (used for both target detection and communication purpose). Another objective of designing new waveforms is to identify suitable solutions for use of spectrum that is not pre-allocated. This ad hoc spectrum access requires waveforms that have minimum out of band emission (to reduce interference to other users of the spectrum).
Applications are related to the development on next generation mobile networks (5G and beyond) capable of delivering more bits of information with the same resources (infrastructures and spectrum), innovative radar systems with enhanced multifunctional performance (more tasks in the same interval of time) and cognitive capabilities (dynamic selection of different waveforms, depending on the scenario and application), and car-to-car or drone-to-drone communications (the same waveform transmitted by device A could deliver at the same time information from device A to device B, but at the same time extract information on device B from its radar echoes such distance, velocity, trajectory).
The ideal candidate should have a degree in Engineering, Physics, or Mathematics, with knowledge of signal processing, ideally applied to radar and communication domains, and of programming and simulation languages (e.g. MATLAB, Simulink). Interested candidates are invited to contact the first supervisor, Dr Fioranelli, to discuss their interests before applying (email@example.com).
The student will benefit from a close partnership with Leonardo Airborne and Space Systems. They will provide training and company material, monthly reviews and advice from the industrial supervisor, annual presentation to the company radar branch of the business, and possible placements at the Leonardo site to implement and test the developed algorithms and waveforms. Leonardo is also sponsoring another PhD student starting this October in the Wireless Communications and Radar Group, plus a larger cohort of students across different universities allowing for mutual knowledge exchange and peer-learning for the students.
- email redacted
- Related URL
- University of Glasgow, School of Engineering
- Glasgow, UK
- Closing Date
- June 30, 2017