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New signal processing in mobile communications based on machine learning techniques (AYGUF2019)

Project Description

While the world is stepping into the 5G era, the demands for higher data throughput and more security will never stop. This requires more efficient signal processing techniques in communications. During the past decades, various advanced signal processing techniques have been proposed, which include mass MIMO, new modulation scheme, full-duplex transmission, cooperative networks etc. These approaches are all in the traditional physical domain so that the performance is limited to physical constraints such as the available spectrum resources and sizes of the devices. This motives researchers to seek solutions beyond the physical domain such as the social network and content-aware data dissemination. While exploring beyond the physical domain shows an attractive scheme in communications, it also brings great challenge. Particularly with the information other than in the physical domain, traditional resource managements can easily see the underline models no longer valid or the optimization tasks computationally prohibitive. In this project, we will investigate machine learning approaches to address these challenges, because the machine learning has the capability to ‘learn’ from complicated system and make the ‘optimum’ decision. The developed technologies would bring new thinking in the signal processing in communications.

Start date: 1 July, 1 October, 1 January, 1 April.

Entry requirements:

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in electronic engineering or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: artificial Intelligence, machine learning, and system identification, programming skills (e.g. Matlab, C, C++ and Python).

How to apply:

All applications are made online, please select the school/department name under the programme name section and include the quote reference number.

Funding Notes

This is an open call for candidates who are sponsored or who have their own funding. If you do not have funding, you may still apply, however Institutional funding is not guaranteed. Outstanding candidates (UK/EU/International) without funding will be considered for funding opportunities which may become available in the School.

Band RB (UK/EU: TBC; international: £22,350).

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