Communications and Signal Processing MSc (Eng)

Digital signal processing (DSP) is at the core of the communications revolution. Research is constantly being carried out to develop new DSP algorithms, allowing mobile broadband services, ‘Internet of Things’ applications and other technologies to be delivered to a growing number of users. Statistical signal processing is also fundamental to all aspects of the parallel robotics revolution, including sensing, localisation and the now ubiquitous discipline of machine learning.

This programme will give you a thorough introduction to all the different aspects of DSP as it relates to the communications landscape, as well as specialist knowledge from your choice of optional modules. Our embedded systems/ FPGA lab will give you hands-on experience using the DSP technology that can be found in cars, robots, cellular phones, GPS and other technologies, and you’ll learn from expert researchers at the forefront of their fields.

You’ll also benefit from specialist industrial lectures, allowing you to relate the theoretical and design aspects of communications and signal processing to practical problems and real-world constraints.

School Facilities

Our School is an exciting and stimulating environment where you’ll learn from leading researchers in specialist facilities. These include our Keysight Technologies wireless communications lab, as well as labs for embedded systems, power electronics and drives, ultrasound and bioelectronics.

There’s also a Terahertz photonics lab, class 100 semiconductor cleanroom, traffic generators and analysers, FPGA development tools, sensor network test beds. We have facilities for electron-beam lithography and ceramic circuit fabrication – and a III-V semiconductor molecular beam epitaxy facility. The Faculty is also home to the £5.5 million EPSRC National Facility for Innovative Robotic Systems, set to make us a world leader in robot design and construction.

Watching this video in China? View this video on Youku.

Accreditation

The MSc is accredited by the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for Further Learning for registration as a Chartered Engineer. Candidates must hold a CEng accredited BEng/BSc (Hons) undergraduate first degree to comply with full CEng registration requirements.

Accreditation is the assurance that a university course meets the quality standards established by the profession for which it prepares its students. For this course, these are the quality standards set by the IET.

Throughout the year you’ll study a set of core modules that give you an in-depth understanding of DSP, wireless communications, optical communications networks and complex issues around network security.

You’ll also select optional modules that are tailored to your own interests or career plans – you could focus on embedded microprocessor systems, high-speed internet architecture or other related topics. To build your understanding of the global electronics industry, you’ll also complete an “industry dissertation”. This could take the form of a business, manufacturing or outsourcing plan, a proposal for research funding or an essay on a specific aspect of the industry.

Over the summer months, you’ll work on your research project. This may give you the chance to work as an integral part of one of our active research institutes, focusing on a specialist topic of your choice and using the appropriate research methods.

Want to find out more about your modules?
Take a look at the Communications and Signal Processing module descriptions for more detail on what you will study.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our Terms and conditions.

For more information and a full list of typical modules available on this course, please read Communications and Signal Processing MSc (Eng) in the course catalogue

Modules

Year 1

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You will have regular contact with them through lectures, seminars, tutorials, small group work and project meetings. Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

On this course you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Assessment

You will be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Entry requirements

A bachelor degree with a 2:1 (hons) in electronic/electrical engineering, computing, mathematics or physics.

Applicants with a high 2:2 (hons) may also be considered if they can demonstrate specific competence in communications theory or practice.

All applicants will need to have GCSE English Language at grade C or above, or an appropriate English language qualification.

We accept a range of international equivalent qualifications. For more information please contact the Admissions Team.

English language requirements

IELTS 6.5 overall, with no less than 6.0 in any component. For other English qualifications, read English language equivalent qualifications.

Improve your English

International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.

This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Engineering (6 weeks) and Language for Science: Engineering (10 weeks). 

If you need to study for longer than 10 weeks, read more about our postgraduate pre-sessional English course.

How to apply

Application deadlines

International applicants: 11 February 2020. Due to competition for places and the volume of applications received, the deadline for international applicants have been brought forward to 11 February 2020. Applicants received after this date will be marked as unsuccessful.

UK/ EU applicants: 10 September 2020. Applicants are encouraged to apply as early as possible.

Apply

This link takes you to information on applying for taught programmes and to the University's online application system.
 
If you're unsure about the application process, contact the admissions team for help.

Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

Admissions policy

Faculty of Engineering and Physical Sciences Postgraduate Admissions Policy 2020

Fees

• UK/EU: £11,000 (total)
• International: £24,000 (total)

Read more about paying fees and charges.

Brexit 
Visit our Brexit page for the latest information on the effect of the UK's exit from the EU on current students and applicants to the University.

For fees information for international taught postgraduate students, read Masters fees.

Additional cost information

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more about additional costs

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

Scholarships available.

On completing this course, you will have obtained the skills that will lead to employment in any area of the communications/signal processing industry including optical networking, DSP design and implementation, cellular mobile, RF planning, broadband systems and general communications research and development.

Graduates from our School have gone on to work for organisations such as the National Grid, Ericsson Telecommunications, ARM, Imagination Technologies, Cisco Systems, AECOM, Deep Sea Electronics, Huawei, Intel Corp., the Technology and Strategy Board and many more.

This course is also an excellent base from which to pursue a PhD and possibly an academic career.

Careers support

You will have access to the wide range of engineering and computing careers resources held by our Employability team in our dedicated Employability Suite. You’ll have the chance to attend industry presentations, book appointments with qualified careers consultants and take part in employability workshops. Our annual STEM Careers Fairs provide further opportunities to explore your career options with some of the UK’s leading employers.

The University's Careers Centre also provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.

The research project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects on the Communications and Signal Processing MSc (Eng) include:

• Powerline communications for smart grid
• Quantum key distribution over passive optical networks
• Physical layer security using artificial noise
• An energy-saving robot mobility diversity algorithm for wireless communications
• Analysis and processing of physiological data from a smart watch to monitor health
• Evaluation of wireless sensor networks for civil engineering applications
• Cooperative wireless communications over fading channels
• Carrier frequency offset compensation in OFDM for IEEE 802.11
• Underlay spectrum access strategy in cognitive radio
• Compressive sensing for channel estimation in massive MIMO
• Deep learning for intrusion detection in software defined networks
• Device-to-device communications in 5G