2024/25 Taught Postgraduate Module Catalogue
ELEC5442M Digital Signal Processing for Communications
15 creditsClass Size: 60
Module manager: Dr Ali Zaidi
Email: S.A.Zaidi@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2024/25
This module is not approved as an Elective
Module summary
This module covers the fundamental principles of digital signal processing, and provides students with the skills to apply DSP techniques to a broad range of signal processing problems. Fundamental concepts in signal processing such as the sampling theorem, analogue-to-digital conversion, and discrete-time signals are explored, and mathematical tools including Discrete-Time Fourier Transform (DTFT), Z-transform, and Discrete Fourier Transform (DFT), are studied with an emphasis on their applications in system analysis and design. The module also introduces digital filter design, adaptive signal processing, and explores real-world DSP applications.Objectives
This module has the following objectives:- To study the core principles of digital signal processing (DSP), covering a broad spectrum of applications in communications.
- To study the mathematical theories of DSP for both analysis and design, applying these techniques to process signals from random processes.
- To evaluate the advantages and disadvantages of various DSP implementations and elucidate how DSP algorithms can optimize the performance of cellular mobile radio systems.
- To foster a deep understanding and practical application, through equipping learners with valuable insights into the diverse aspects of DSP in communication contexts
Learning outcomes
On successful completion of the module students will have demonstrated the following learning outcomes:
1. Apply a comprehensive knowledge of mathematics, statistics, and engineering principles to the solution of complex problems.
2. Formulate and analyse complex problems to reach substantiated conclusions. This will involve evaluating available data using first principles of mathematics, statistics, and engineering principles.
3. Select and apply appropriate computational and analytical techniques to model complex problems, discussing the limitations of the techniques employed.
Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills:
a) Application of science, mathematics and/or engineering principles
b) Problem analysis
c) Application of computational and analytical techniques
Syllabus
• Brief history of DSP and advantages of modern DSP applications
• The sampling theorem, analogue-to-digital conversion, quantisation and limitations of DSP
• Discrete-time signals and systems, linear convolution, linear difference equations (LDEs) and system frequency response
• Discrete-Time Fourier Transform (DTFT), Z-transform, system pole/zero plots and stability analysis
• Discrete Fourier Transform (DFT) and its relationship to circular convolution/OFDM/fast linear convolution/spectral analysis
• The Fast Fourier Transform (FFT)
• Introduction to discrete-time modelling, digital filter design, random processes and adaptive signal processing
• Case studies taken from: wireless channel estimation/equalisation, linear predictive coding for speech compression, interpolation/decimation/multirate structures, MIMO signal processing applications, quadrature DSP, direction of arrival (DoA) estimation, software defined radio (SDR) and DSP applied to music
Methods of Assessment
We are currently refreshing our modules to make sure students have the best possible experience. Full assessment details for this module are not available before the start of the academic year, at which time details of the assessment(s) will be provided.
Assessment for this module will consist of;
2 x Exam
Teaching methods
Delivery type | Number | Length hours | Student hours |
Example Class | 2 | 2.00 | 4.00 |
Lecture | 8 | 2.00 | 16.00 |
Independent online learning hours | 25.00 | ||
Private study hours | 105.00 | ||
Total Contact hours | 20.00 | ||
Total hours (100hr per 10 credits) | 150.00 |
Methods of assessment
Coursework
Assessment type | Notes | % of formal assessment |
In-course Assessment | In-class Test 1 | 30.00 |
Total percentage (Assessment Coursework) | 30.00 |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Exams
Exam type | Exam duration | % of formal assessment |
Standard exam (closed essays, MCQs etc) | 3 hr 00 mins | 70.00 |
Total percentage (Assessment Exams) | 70.00 |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading list
There is no reading list for this moduleLast updated: 12/09/2024
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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