Wireless and Computer Communication Networks MSc

Compulsory

• Communication Networks Security
  This module enable graduate to acquire an important aspect of future networks concentrating on cryptography and secure communication networks.
• Communication Network Technologies
  This module will focus on advanced communication technologies and networks. Indicative contents: Network Basics: ISO/OSI Reference Model and TCP/IP Reference Model, Network layer operation: TCP/IP, Packet Scheduling and Delay, IP Quality of Services (QoS), Resource Reservation Protocol (RSVP), Integrated Service Model and Differentiated Service Model, Multi-Protocol Label Switching (MPLS), ATM Networks, Traffic Engineering IP Multicasting Mobile and wireless communication systems: Cellular system, Frequency reuse, 1st and 2nd generation systems, 2 and 2.5 G (GSM, GPRS, EDGE), UMTS-3G, (UTRAN, Core Networks, Handover, Power Control, Rake receiver), 4G (LTE – Advanced, S/P, IFFT, CP, P/S), 5G (Introduction, C-RAN, MIMO), ZIGBEE, UWB, Bluetooth. Ad-hoc and Mesh Networks: Introduction to mesh networks, power spectral efficiency and green radio, Mesh network Components, Ad-Hoc Routing protocols.
• Design for Internet of Things
  The aim of the module is equip students with topics in digital communication systems and Internet of Things (IoT) technologies. The indicative content includes, Coding and Compression, Modulation Schemes, Propagation and Channel Modelling, MIMO Systems, IoT Systems Architectures, IoT Physical Connectivity.
• Engineering Ethics and Sustainability
  This module aim to enable Engineering students to deal with legal, social, ethical and environmental issues and apply professional codes of conduct. Indicative content: Ethics and Legal Aspects, Risk and environment management systems, Risk Assessment and engineering failure methods and sustainability.
• Artificial Intelligence System Techniques
  The aim of the module is: To understand the full range of state-of-the-art artificial intelligence systems techniques; To raise critical awareness of the issues affecting the performance of artificial intelligence systems; To develop the skills required to develop artificial intelligence applications; To gain hands-on experiences through learning, applying and implementing artificial intelligence systems to a given simulated system. The indicative content includes, Overview of artificial intelligence systems techniques, Intelligent Computation Techniques (Fuzzy Logic: Concepts, Membership functions, Inference methods and design; Neural Networks (NN): Representations, Topologies, Deep Learning techniques; Neuro-Fuzzy Systems (NF): Design, Topology, Training, Comparison to NN; Genetic Algorithms: Representations, Genetic operators, Selection schemes, Fitness & population evaluation, Constraint handling, Learning and evolution; Swarm Intelligence: Particle swarm, Ant Colony optimisation), Intelligent Data Processing Techniques, Applications (Wireless and computer networks, Bioinformatics, Medical imaging & visualisation, Pattern recognition & biometrics, Computer vision, Future trends).
• Radio and Optical Communication Systems
  This module aims to consider the operation of radio and optical frequency systems and their integration into global systems for effective communications.
• Project and Dissertation
  This module aims to provide experience in defining and organising, executing and evaluating a substantial individual in-depth investigation into a topic related to the appropriate wireless and computer communication networks and presenting the information in the form of a dissertation.

Optional

• Embedded DSP for Communication Systems
  The aim of the module is develop in-depth knowledge and understanding of real-time signal processing, reconfigurable computing and embedded DSP system architecture and to develop students’ ability to implement real time algorithms on embedded DSP processors for communication applications.
• Advanced Embedded Systems Design
  The aims of this module are to: 1. provide a detailed knowledge of computing for embedded and control computer systems; 2. illustrate and develop an understanding of the various engineering, scientific and economic trade-offs necessary in the design of embedded systems; 3. understand the principles and the role of embedded systems in real world applications; 4. provide familiarity and experience with a range of architectural and programming techniques for embedded engineering systems and their evaluation; 5. understand the process of implementing algorithms on embedded systems.
• Applied Sensors Instrumentation and Control
  This module aims to enable students to focus on particular aspects of sensors, instrumentation and control through the use of real-world examples and hence to acquire knowledge and understanding of the characteristics of sensors and associated systems for monitoring and control, and the skills to evaluate, design and implement them.