MSc Intelligent Communication Systems and Networks

1 Years On Campus Masters Program

University of Surrey

Program Overview

The MSc Intelligent Communication Systems and Networks at the University of Surrey equips students with advanced skills in artificial intelligence, machine learning, and communications engineering. It is ideal for those who want to design next-generation networks, from 5G/6G systems to secure and intelligent IoT infrastructures.

Curriculum Structure

Core Phase: Students take foundational modules such as Fundamentals of Machine Learning for Communications, Wireless Communication Principles, and Network Planning and Management. They gain expertise in AI/ML applications, signal propagation, and network design principles.
Specialisation Phase: Optional modules include Radio Frequency Engineering and Antennas, Network Security, Advanced Wireless Techniques, and Artificial Intelligence of Things, enabling students to tailor their learning toward RF design, secure communications, or smart network systems.
Final Project Phase: In the final phase, students complete a major individual project, applying AI-driven solutions or network design techniques to a real-world communication challenge, culminating in a prototype or research report.

Focus Areas

AI-driven communication systems, intelligent networks, 5G/6G and wireless protocols, network security, RF engineering, IoT communications.

Learning Outcomes

Graduates will be able to apply machine learning to communication system design, plan and optimise network deployments, analyse RF and antenna systems, design secure communication architectures, and complete a substantial research-oriented project.

Professional Alignment (Accreditation)

The MSc aligns with professional engineering standards and is accredited by the Institution of Engineering and Technology (IET), supporting pathways to Chartered or Incorporated Engineer status.

Reputation (Employability / Rankings)

The University of Surrey is renowned for its research excellence in next-generation communications, including the 5G/6G Innovation Centre. Graduates are highly sought after for roles in telecommunications, network planning, AI-based communication design, and security engineering.

Experiential Learning (Research, Projects, Internships etc.)

The MSc in Intelligent Communication Systems & Networks at Surrey is engineered to blend advanced communications technology with AI and machine learning, letting students work on both hardware and software in a deeply practical way. Students benefit from Surrey’s world-leading research facilities and testbeds — particularly in the 5G/6G Innovation Centre — which provide real-world platforms to experiment, simulate, and prototype next-generation communication systems. They work on group projects, use simulation tools and live network testbeds, and complete a significant individual research or design project in their final term.

Some of the hands-on opportunities include:

Design and simulation of communication networks using industry-level tools, focusing on 5G, 6G, IoT, and AI-driven networks.
Practical exposure to machine learning for communications, where students train and test ML/AI models for application in real network problems.
Use of testbed hardware and real communication infrastructure to validate protocols, network planning, and deployment strategies.
A substantial individual MSc project, letting students explore a topic of their choice — for example, AI for network security, intelligent routing, or radio-frequency design.
Collaboration with peers on group coursework, giving insight into team-based engineering and project management.
Development of digital skills (e.g., MATLAB, Python) as part of assignments and modelling.

Key Modules

Some of the core and optional modules in the MSc are:

Fundamentals of Machine Learning for Communications – Covers supervised, unsupervised, and reinforcement learning, applied to communication systems.
Digital Communications – Principles of digital modulation, coding, and system design.
Artificial Intelligence of Things (optional) – Focuses on AI-integrated IoT networks and distributed intelligence.
Network Planning & Management – Algorithms, protocols, and strategies for designing reliable and efficient networks.
Network Security (optional) – Exploring security challenges in modern intelligent networks, including wireless and IoT contexts.
Radio Frequency Engineering & Antennas (optional) – Study of RF design, propagation, and antenna systems for next‑gen communications.
MSc Project / Dissertation – A self-driven research or design initiative applying AI and communications to a real‑world problem.

Progression & Future Opportunities

Graduates from this program are well-prepared for roles in communication technology, network engineering, and intelligent systems development:

University services supporting employment: The Surrey Careers Service offers personalised guidance, industry networking events, technical workshops, and support for internships and graduate employment.
Employment stats and salary figures: Early career salaries typically range from £30,000 to £50,000, with progression to senior or specialist network engineering roles leading to higher earnings.
University–industry partnerships: The program benefits from collaborations with leading telecommunications companies, IoT developers, and technology research centres, providing project opportunities, placements, and exposure to emerging technologies.
Long-term accreditation value: The program supports progression toward professional recognition, including Chartered Engineer (CEng) status for eligible graduates.
Graduation outcomes: Alumni often secure positions such as Network Engineer, Communications Systems Engineer, IoT Systems Developer, or Wireless Communications Specialist.

Further Academic Progression:
Graduates can pursue research degrees such as a PhD in Communication Systems, Network Engineering, or Intelligent Systems, or specialised postgraduate certifications in areas like 5G networks, IoT, or cyber-physical systems.