Information in the Degree Programme Tables may still be subject to change in response to Covid-19

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Engineering : Postgrad (School of Engineering)

Postgraduate Course: Array Processing and MIMO Systems (MSc) (PGEE11124)

Course Outline
SchoolSchool of Engineering CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThis course will cover the current topics of interest in Array Processing and MIMO systems.
1) Introduction
2) Signal Model (1D and 2D or 3D arrays)
3) Different types of Beamforming
4) Different techniques for source Localisation including subspace methods
5) Detection of number of signals
6) MIMO Systems: Channel Modelling and Spatial Multiplexing
7) Maximum Likelihood Parameter Estimation

Practical examples of the above concepts are presented throughout the course.
Course description Lectures and tutorials
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Discrete-Time Signal Analysis (PGEE11026) AND Probability, Estimation Theory and Random Signals (PETARS) (MSc) (PGEE11164)
Co-requisites Students MUST also take: Digital Signal Processing Laboratory (MSc) (PGEE11108)
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2020/21, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 22, Seminar/Tutorial Hours 11, Formative Assessment Hours 1, Summative Assessment Hours 4, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 60 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% Coursework

60% online exams and 40% MATLAB coursework.
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand the modelling of the array received signals for 1D, 2D and 3D arrays. Understand the fundaments concepts of beamforming techniques such as conventional, optimum and adaptive beamformers, Capon method, MSE based beamforming, LCMV beamformers
  2. Understand the fundamental concepts of source localisation techniques such as conventional techniques, subspace methods, i.e., MUSIC, Root- MUSIC, ESPRIT. Understand the concept of source detection techniques such as MDL and AIC methods.
  3. Develop a unified way of modelling the MIMO and mmWave channels using array processing concepts.
  4. Quantify the MIMO wireless channel capacities and degrees of freedom regions for different channel models, such as multiple access channels, broadcast channels, interference channels, etc.
  5. Understand the concepts of Maximum Likelihood Parameter Estimation techniques
Reading List
1) P. Stoica and R. Moses, Spectral Analysis of Signals, Prentice Hall, 2005. Chapter 6 (

2) D. Tse and P. Viswanath, Fundamentals of Wireless Communications, Cambridge University Press, 2005

3) S. U. Pillai, Array Signal Processing, Springer-Verlag, 1989.
Additional Information
Graduate Attributes and Skills Not entered
KeywordsNot entered
Course organiserProf Tharmalingam Ratnarajah
Tel: (0131 6)50 5578
Course secretaryMiss Jo Aitkenhead
Tel: (0131 6)50 5532
Help & Information
Search DPTs and Courses
Degree Programmes
Browse DPTs
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Important Information