Skip to main content


EEE8128 : Communications and Signal Processing (Coursework)

  • Offered for Year: 2022/23
  • Module Leader(s): Dr Charalampos Tsimenidis
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semester 1 Credit Value: 20
ECTS Credits: 10.0


To ensure students have a sound knowledge of the fundamental concepts of simulation techniques for wireless communication systems.

To provide experience and develop skills in the simulation of communication systems using MATLAB.

To develop skills in mapping theoretical concepts to fast signal processing algorithms as required for modern wireless communications.

To ensure students can assess the complexity involved in the computation of digital signal processing algorithms and be able to recommend hardware specifications that meet the requirements.

Outline Of Syllabus

Part A
The bit error rate (BER) performance of a digital communication link using a state-of-the-art modulation scheme such as high order Quadrature Amplitude Modulation (QAM) in conjunction with Orthogonal Frequency Division Multiplexing (OFDM) will be investigated via MATLAB simulations in mobile wireless communications channels and in the presence of additive white Gaussian noise (AWGN) by utilizing functions available in the Signal Processing and Communications toolboxes and additional programming. Initially, an introduction to MATLAB will be offered where the students will be familiarised with the MATLAB development cycle. The simulation test bench will be implemented in the complex based-band and will include the following functionality:
1.       16-QAM information bit/symbol generator.
2.       16-QAM modulator that maps information bits/symbols to the 16-QAM constellation.
3.       OFDM modulator including provision for cyclic prefix (CP) protection against multipath channel spread.
4.       ITU based frequency-selective multipath channel and complex-valued AWGN generator.
5.       Optimal receiver for AWGN.
6.       Zero-forcing (ZF) and Minimum Mean Squared Error (MMSE) based equalizers to combat the multipath channel.
7.       Computation of BER performance for various CP length as a function of signal to noise ratio (SNR) using the known channel impulse response (CIR) against their semi-analytical performances.
8.       CIR computation using comb pilot based channel estimation (CE).
9.       BER and Mean Squared Error (MSE) performance for CE based ZF and MMSE equalizers.
10.       Improved simulation speeds using cluster-type parallel computation.

Part B
Extension to multiple-input multiple-output systems as used in 5G cellular communications will be considered by extending the functionality of the simulation to accommodate for
1.       Multiple OFDM transmitters and receivers.
2.       Generation of 5G compatible wireless channels.
3.       3D matrix operations in Matlab.
4.       MIMO channel channel impulse response (CIR) simulation and frequency response computation.
5.       Noise variance computation for setting Signal-to-noise Ratio (SNR) in MIMO systems.
6.       MIMO ZFE and MMSE receiver computation and applications per subcarrier dimension.
7.       Computations of BER for different Tx and Rx dimensions.
8.       Computational complexity analysis for receiver operations.
9.       Theoretical and semi-analytical performance analysis for MIMO OFDM systems.
10.       Parallel computation implementation for speeding-up simulations.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion135:0035:00OFDM assignment in MATLAB and writing of report.
Guided Independent StudyAssessment preparation and completion110:0010:00Preparation of software code for computer assessment.
Structured Guided LearningAcademic skills activities201:0020:00Preferably Lab-based activities (PiP): Real-time DSP implementation of wireless receiver algorithms
Guided Independent StudySkills practice135:0035:00MIMO assignment and writing of report.
Guided Independent StudySkills practice135:0035:00Software development skills, in students own time.
Structured Guided LearningStructured non-synchronous discussion200:3010:00Non-synchronous pre-recorded video lectures.
Guided Independent StudyIndependent study135:0035:00Review of lecture notes and general reading.
Scheduled Learning And Teaching ActivitiesScheduled on-line contact time201:0020:00Lectures (PiP) delivered preferably in class or online
Teaching Rationale And Relationship

The module will be taught via pre-recorded lectures that introduce the required background knowledge and give the students guidance on how to implement in MATLAB the different stages of the communication links under consideration. Each programming activity (1/2 hour) will be supported by a 1/2 hour lecture, where the the theory behind the tasks to be completed is introduced, and the programming methods and software tools to be utilized are outlined. A set of guidance notes is also provided. Additional support will be provided by interleaved online Q&A sessions. The simulation techniques and software implementation of communication and DSP systems is most effectively taught with this hands-on approach, allowing the students to discover how signal processing theory can be applied in practice and how to diagnose problems. The students also have significant scope to show initiative and to investigate a variety of solutions to a given problem.

Alternatives will be offered to students unable to be present-in-person due to the prevailing C-19 circumstances. Student’s should consult their individual timetable for up-to-date delivery information.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report1M75Part A/B: OFDM simulation and MIMO, 3000 word report to be submitted online.
Computer assessment1M25MATLAB code development and implementation.
Assessment Rationale And Relationship

The module is assessed via report writing and software code development. Report writing assesses the understanding of underlying theoretical concepts, while simulation, implementation and modelling is assessed via software code development in Matlab. The programming sessions consider the various concepts explained in the lectures and provide students with several practical problems encountered by R&D engineers in the telecommunication industry.

Reading Lists