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Signal Processing for Communications - ELE00092M

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  • Department: Electronic Engineering
  • Module co-ordinator: Dr. Yury Zakharov
  • Credit value: 20 credits
  • Credit level: M
  • Academic year of delivery: 2018-19

Module summary

The purpose of this module is to provide a thorough understanding of signal processing techniques used in communication systems.

Module will run

Occurrence Teaching cycle
A Spring Term 2018-19

Module aims

Subject content aims:

  • To introduce the fundamental techniques of digital signal processing relevant to telecommunications.
  • To allow students to apply those techniques to design problems

Graduate skills aims:

  • Conduct original research into communications engineering theory and practice, advancing the state of knowledge by applying specialist knowledge of wireless communication techniques and systems.
  • Extract and critically evaluate data from complex communication systems through analytical and computational methods and modelling.
  • Design innovative industry relevant engineering solutions for research-based problems in communications software and/or hardware.
  • Apply professional skills in communications theory, programming, modelling, combined with an understanding of engineering and communication systems and components, to independently solve technically challenging problems.

Module learning outcomes

  • Subject content learning outcomes

    After successful completion of this module, students will:

  • Understand the place of digital signal processing in communication systems.
  • Understand channel models used in design and testing of communication systems.
  • Understand elements of estimation and detection theory relevant to the channel estimation, synchronisation, and data detection.
  • Understand optimal signal processing, including the optimal detection, matching filtering, adaptive filtering, LMS, and applications.
  • Understand signal processing techniques used for the phase and timing synchronisation.
  • Understand channel estimation and equalisation techniques.
  • Understand diversity systems, including the maximal ratio combining.
  • Understand multiuser detection.
  • Understand how the signal processing techniques are used in practical communications systems.
  • Graduate skills learning outcomes

    After successful completion of this module, students will:

  • Be able to apply theoretical knowledge to development of communication systems at the physical layer level.

Assessment

Task Length % of module mark
University - closed examination
Signal Processing for Communications
2.5 hours 100

Special assessment rules

None

Reassessment

Task Length % of module mark
University - closed examination
Signal Processing for Communications
2.5 hours 100

Module feedback

Students will receive indicative marks and feedback on the examination performance within four weeks.

Indicative reading

  • Meyr, H, Moeneclaey, M, and Fechtel, SA, 'Digital Communication Receivers. Synchronization, Channel Estimation, and Signal Processing', John Wiley & Sons, 1998, ISBN 0-471-50275-8.
  • Ifeachor, EC, & Jervis, BW, 'Digital Signal Processing: A Practical Approach', Addison Wesley, 1993. ISBN 0-201-54413-X.
  • Verdu, S, 'Multiuser detection', Cambridge University Press, 1998. ISBN 0-521-59373-5.
  • Proakis, J.D., 'Digital Communications' New York; McGraw-Hill, 1995



The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.

Coronavirus (COVID-19): changes to courses

The 2020/21 academic year will start in September. We aim to deliver as much face-to-face teaching as we can, supported by high quality online alternatives where we must.

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