Telecommunications Engineering MSc

You'll gain a comprehensive and advanced understanding of digital communication techniques for data and voice within communication systems. You'll be introduced to a detailed coverage of source coding, channel coding, baseband and bandpass digital modulation and demodulation techniques, detection theory and error analysis, spread spectrum signals and multiuser communications, wireless fading channels, channel equalization techniques, and advanced topics in multiple antenna array, 5G/6G enabling technologies. These topics will equip you with the knowledge, skills and ability to understand, compare and critically evaluate the advantages and limitations of modern digital techniques within communication systems and wireless technologies. You'll also be able to learn and apply analytical skills to perform system performance analysis with practical observations through simulation and laboratory experiences.

The aim of this module is to provide you with a comprehensive technical foundation of the mobile communication systems and wireless network architectures and services. You'll learn topics like, fundamental aspects of signals, concept of cellular systems and the evolution towards next generation networks, other wireless technology systems and networks, mobility aspects in wireless communications and recent advancements such as millimetre wave multi-gigabit wireless networks.

Throughout this module you will learn how to evaluate a network situation and identify the most important aspects to monitor and analyse. You will be introduced to a methodological approach to network design and the concepts of network modelling, analysis and simulation. At the end of the module you will have developed an appreciation of the design and development simulation software as appropriate models to evaluate the pure performance and availability, as well as the performability, of computer networks.

This module covers the principles and foundations of network security. It aims at providing you with the knowledge of security issues, technologies, algorithms and protocols used in securing computer networks and associated systems. It will also provide an understanding of possible security breaches, security risk analysis and mechanisms to protect computer and network communication systems.

This module aims to introduce you to the paradigms of intelligence based networked systems and in particular Internet of Things (IoT), both theoretically and practically. You'll be introduced to the technology and architectures that create IoT and enables intelligent habitation, intelligent building control, smart vehicle technology and industrial processes.

You'll learn to provide a critical overview of the research methods and tools required for the planning and management of a dissertation project. You'll aid in formulation of a research problem and identifying literature, in addition to conducting research project in well-equipped laboratory facilities for the simulation and analysis of wireless and mobile communications technology. The project will enable you to demonstrate a personal commitment to professional standards and develop expertise in the planning and execution of extensive research investigation in a specialised area of Wireless Communications and Networks. This module will prepare you for future employment in the Telecommunications sector at an advanced technical level.

As well as developing your practical skills in laboratory sessions, you’ll attend interactive lectures, seminars, workshops and tutorials, where you’ll deepen your theoretical knowledge, work on activities and case studies, and develop your analytical and problem-solving skills.

You will do research and design work, produce written reports, give presentations and take part in group discussions and group work, supplementing all this with your own independent study.

You'll be taught by an experienced teaching team with a wide range of expertise and professional experience.

You will be based at our north London campus with most of the activities based in the Ritterman Building.

Whether you are studying full or part-time – your course timetable will balance your study commitments on campus with time for work, life commitments and independent study.

We aim to make timetables available to students at least 2 weeks before the start of term. Some weeks are different due to how we schedule classes and arrange on-campus sessions.

In a typical year, you’ll spend about 1200 hours on your course.

Outside of teaching hours, you’ll learn independently through reading articles and books, working on projects, undertaking research, and preparing for assessments including coursework and presentations.

Typical weekly breakdown

A typical week looks like this:

For placement, there may be additional hours.

Learning terms

On-campus: This includes tutor-led sessions such as seminars, lab sessions and demonstrations as well as student-led sessions for work in small groups.

Online learning: This is teaching that is delivered online using tools like Skype or Zoom, as well as work that you do yourself using online teaching resources.

Independent study: This is the work you do in your own time including reading and research.

Part-time study

You can also study this course part-time.

We have a strong support network online and on campus to help you develop your academic skills. We offer one-to-one and group sessions to develop your learning skills together with academic support from our library, IT teams and learning experts.

Throughout the year, we'll assess your technical skills through a series of assignments. Every week, we'll give you lab tasks designed to match the content covered in the lecture. We expect these tasks to be completed during the lab and you'll receive timely feedback assessment.

We'll assess your understanding through a variety of assessment methods including coursework projects, in-class activities, and a portfolio of data science tasks.

You'll evaluate your work, skills and knowledge and identify areas for improvement. Sometimes you'll work in groups and assess each other's progress (peer-based).

Each term, you'll get regular feedback on your learning.