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IMPORTANT: The second assessment pattern is only applicable to the MSc Short Course Students Expected prior learning: EEE3033 – RF and Microwave Fundamentals, or equivalent learning. Module purpose: Advanced communications systems and radar operate at RF and microwave frequencies. The design principles and circuit operation, underlying these systems, are quite different from those of electronics used in signal processing at baseband frequencies. This module will cover the key elements of RF and microwave system design as well as analysis concepts for a range of commonly used active circuits, including: oscillators, frequency synthesisers, amplifiers and mixers. The module will also cover the circuit design and operation of non-linear devices used in active circuits together with deployment considerations. This module will include and build on many of the concepts studied in EEE3033 RF and Microwave Fundamentals and address further advanced features of non linear RF devices and system optimisation. It is complementary to EEEM064 Microwave Design Techniques and also EEEM006 Antennas and Propagation.

Expected prior learning:  None specifically advised. Module purpose:  Earth and planetary observation with remote sensing data is playing a key role in the present understanding of natural phenomena, prevention of disasters, resources monitoring, comprehension of origins of life. Through a series of lectures, seminars, open discussions and “thinking breaks” in class, the module aims to give an introduction to the scientific principles of remote sensing – both passive and active – as carried out by spacecraft. Remote sensing is discussed in terms of instrumentation, missions, products and applications. IMPORTANT: The Second assessment pattern (Written Exam) is only applicable to the MSc Short Course Students.

Module purpose: Advances related to energy efficiency issues and cost reductions have resulted in the rapid growth and deployment of networked devices and sensing/actuation systems that connect the physical world with the cyber world. This evolving framework, now recognized as the Artificial Intelligence of Things (AIoT), integrates IoT technologies with artificial intelligence (AI) to enhance automation, intelligence, and decision-making. AIoT incorporates several cutting-edge technologies, including wireless sensor networks, pervasive systems, ambient intelligence, context awareness, distributed systems, and machine learning-driven analytics. Module Overview: The advanced AIoT module is designed to provide a comprehensive understanding of how machine communications , coupled with AI, contribute to creating smart artificial intelligence-driven environments, focusing on networking and communication systems. The module provides an overview of the key concepts and enabling technologies for AIoT. It encompasses a cross-layer approach, allowing students to explore the practical aspects of sensors, actuators, and mainly communication systems for AIoT across physical, media access, and network layers. This includes security considerations, satellite AIoT, positioning and tracking for industrial applications, AIoT Platforms (Hardware, Software), protocols and standards (e.g. 6LowPAN, ZigBee, CoAp), semantic technologies, and data and information processing mechanisms. Also, the module explores AI-driven methodologies such as ensemble learning, multi-armed bandits for sequential decision-making, and lightweight machine learning Mmodels for AIoT applications. These techniques enhance real-time data analysis, predictive maintenance, anomaly detection, and adaptive control while ensuring computational efficiency.

This module offers a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML) with a focus on its applications in modern communication systems. By taking this module, the student builds a strong foundation of AI/ML starting from the mathematical basics (linear algebra, probability, optimization) and the main algorithms and models (e.g. Decision Trees, Support Vector Machines, Deep Neural Networks, etc.) to the modern generative models, and reinforcement learning. Through the coursework, the student will gain hands-on experience with key AI/ML models applied to modern communication systems. By the end of the module, the student will not only understand the theory of machine learning but also develop the practical skills needed to implement and evaluate models for real-world applications in communications.

This module offers a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML) with a focus on its applications in modern communication systems. By taking this module, the student builds a strong foundation of AI/ML starting from the mathematical basics (linear algebra, probability, optimization) and the main algorithms and models (e.g. Decision Trees, Support Vector Machines, Deep Neural Networks, etc.) to the modern generative models, and reinforcement learning. Through the coursework, the student will gain hands-on experience with key AI/ML models applied to modern communication systems. By the end of the module, the student will not only understand the theory of machine learning but also develop the practical skills needed to implement and evaluate models for real-world applications in communications.

Expected prior learning: Module EEE2040 – Communications Networks or equivalent learning. Module purpose: The Internet is an important worldwide communications system; the module provides an in-depth treatment of current and evolving Internet protocols and standards, and the algorithms that underlie them. The module also permits further study on networking in modules such as EEEM018 Advanced Mobile Communication Systems, EEEM023 Network Service management and Control, EEEM032 Advanced Satellite Communication Techniques

IMPORTANT: The second assessment pattern is only applicable to the MSc Short Course Students Expected prior learning: None. Module purpose: Antennas and the propagation of radio on the physical layer (PHY) are a fundamental aspect of communications, space and radar as well as any other device that will radiate electromagnetic waves over an air interface. In order for wireless devices to operate and comply with suitable standards, it is important that they use a suitable antenna design, while also modelling the propagation environment the device may encounter is important for purposes of testing the radio transceiver, thus knowledge of propagation modelling is required to achieve this.  

The module introduces general information and network security principles, challenges and goals and then focuses on main security mechanisms and protocols for protecting network communication across different layers of the Internet protocol stack. This will include discussion on various attacks on the networks, penetration testing tools and possible countermeasures to ensure protection of authentication, confidentiality and end-to-end security of communications. In labs students will be able to practice experience with various network security protocols and tools.

Expected prior learning: EEE3033–RF and Microwave Fundamentals, or equivalent learning. Module purpose: At Gigahertz frequencies the operating wavelength is small. Devices operating in the Gigahertz frequency range are therefore electrically large compared to the operating wavelength. In such cases, it is no longer appropriate to use traditional lumped element circuit components. The passive devices used at Gigahertz frequencies thus have to be made either using printed transmission lines (e.g. microstrip, coplanar waveguide) or waveguide. This module will present microwave design and analysis concepts for a range of commonly used passive circuits using both microstrip lines and waveguides, including: transmission lines, coupling networks, antennas and filters. This module will revisit and build on the use of the Smith chart also introduced in EEE3033 RF and Microwave Fundamentals and use it for further design applications of microstrip circuits. It is complementary to module EEEM044 RF Systems and Circuit Design and EEEM006 Antennas and Propagation.

IMPORTANT: The second assessment pattern is only applicable to the MSc Short Course Students Expected prior learning: EEE3033 – RF and Microwave Fundamentals, or equivalent learning. Module purpose: Advanced communications systems and radar operate at RF and microwave frequencies. The design principles and circuit operation, underlying these systems, are quite different from those of electronics used in signal processing at baseband frequencies. This module will cover the key elements of RF and microwave system design as well as analysis concepts for a range of commonly used active circuits, including: oscillators, frequency synthesisers, amplifiers and mixers. The module will also cover the circuit design and operation of non-linear devices used in active circuits together with deployment considerations. This module will include and build on many of the concepts studied in EEE3033 RF and Microwave Fundamentals and address further advanced features of non linear RF devices and system optimisation. It is complementary to EEEM064 Microwave Design Techniques and also EEEM006 Antennas and Propagation.

Expected prior learning:  None specifically advised. Module purpose:  Earth and planetary observation with remote sensing data is playing a key role in the present understanding of natural phenomena, prevention of disasters, resources monitoring, comprehension of origins of life. Through a series of lectures, seminars, open discussions and “thinking breaks” in class, the module aims to give an introduction to the scientific principles of remote sensing – both passive and active – as carried out by spacecraft. Remote sensing is discussed in terms of instrumentation, missions, products and applications. IMPORTANT: The Second assessment pattern (Written Exam) is only applicable to the MSc Short Course Students.

Module purpose: Advances related to energy efficiency issues and cost reductions have resulted in the rapid growth and deployment of networked devices and sensing/actuation systems that connect the physical world with the cyber world. This evolving framework, now recognized as the Artificial Intelligence of Things (AIoT), integrates IoT technologies with artificial intelligence (AI) to enhance automation, intelligence, and decision-making. AIoT incorporates several cutting-edge technologies, including wireless sensor networks, pervasive systems, ambient intelligence, context awareness, distributed systems, and machine learning-driven analytics. Module Overview: The advanced AIoT module is designed to provide a comprehensive understanding of how machine communications , coupled with AI, contribute to creating smart artificial intelligence-driven environments, focusing on networking and communication systems. The module provides an overview of the key concepts and enabling technologies for AIoT. It encompasses a cross-layer approach, allowing students to explore the practical aspects of sensors, actuators, and mainly communication systems for AIoT across physical, media access, and network layers. This includes security considerations, satellite AIoT, positioning and tracking for industrial applications, AIoT Platforms (Hardware, Software), protocols and standards (e.g. 6LowPAN, ZigBee, CoAp), semantic technologies, and data and information processing mechanisms. Also, the module explores AI-driven methodologies such as ensemble learning, multi-armed bandits for sequential decision-making, and lightweight machine learning Mmodels for AIoT applications. These techniques enhance real-time data analysis, predictive maintenance, anomaly detection, and adaptive control while ensuring computational efficiency.

This module offers a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML) with a focus on its applications in modern communication systems. By taking this module, the student builds a strong foundation of AI/ML starting from the mathematical basics (linear algebra, probability, optimization) and the main algorithms and models (e.g. Decision Trees, Support Vector Machines, Deep Neural Networks, etc.) to the modern generative models, and reinforcement learning. Through the coursework, the student will gain hands-on experience with key AI/ML models applied to modern communication systems. By the end of the module, the student will not only understand the theory of machine learning but also develop the practical skills needed to implement and evaluate models for real-world applications in communications.

This module offers a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML) with a focus on its applications in modern communication systems. By taking this module, the student builds a strong foundation of AI/ML starting from the mathematical basics (linear algebra, probability, optimization) and the main algorithms and models (e.g. Decision Trees, Support Vector Machines, Deep Neural Networks, etc.) to the modern generative models, and reinforcement learning. Through the coursework, the student will gain hands-on experience with key AI/ML models applied to modern communication systems. By the end of the module, the student will not only understand the theory of machine learning but also develop the practical skills needed to implement and evaluate models for real-world applications in communications.

Expected prior learning: Module EEE2040 – Communications Networks or equivalent learning. Module purpose: The Internet is an important worldwide communications system; the module provides an in-depth treatment of current and evolving Internet protocols and standards, and the algorithms that underlie them. The module also permits further study on networking in modules such as EEEM018 Advanced Mobile Communication Systems, EEEM023 Network Service management and Control, EEEM032 Advanced Satellite Communication Techniques

IMPORTANT: The second assessment pattern is only applicable to the MSc Short Course Students Expected prior learning: None. Module purpose: Antennas and the propagation of radio on the physical layer (PHY) are a fundamental aspect of communications, space and radar as well as any other device that will radiate electromagnetic waves over an air interface. In order for wireless devices to operate and comply with suitable standards, it is important that they use a suitable antenna design, while also modelling the propagation environment the device may encounter is important for purposes of testing the radio transceiver, thus knowledge of propagation modelling is required to achieve this.  

The module introduces general information and network security principles, challenges and goals and then focuses on main security mechanisms and protocols for protecting network communication across different layers of the Internet protocol stack. This will include discussion on various attacks on the networks, penetration testing tools and possible countermeasures to ensure protection of authentication, confidentiality and end-to-end security of communications. In labs students will be able to practice experience with various network security protocols and tools.

Expected prior learning: EEE3033–RF and Microwave Fundamentals, or equivalent learning. Module purpose: At Gigahertz frequencies the operating wavelength is small. Devices operating in the Gigahertz frequency range are therefore electrically large compared to the operating wavelength. In such cases, it is no longer appropriate to use traditional lumped element circuit components. The passive devices used at Gigahertz frequencies thus have to be made either using printed transmission lines (e.g. microstrip, coplanar waveguide) or waveguide. This module will present microwave design and analysis concepts for a range of commonly used passive circuits using both microstrip lines and waveguides, including: transmission lines, coupling networks, antennas and filters. This module will revisit and build on the use of the Smith chart also introduced in EEE3033 RF and Microwave Fundamentals and use it for further design applications of microstrip circuits. It is complementary to module EEEM044 RF Systems and Circuit Design and EEEM006 Antennas and Propagation.