Master of Science in Communications Engineering

Master (Coursework)

Programme Type

Full-time, Part-time

The MSc (Communications Engineering) is designed for aspiring engineers and information technologists who wish to improve their knowledge and skills in the broad area of communications engineering.



The courses offered cover various important topics in telecommunications, RF engineering and wireless communications.

Have a good relevant bachelor's degree

Relevant working experience is an advantage

For applicants whose native language is not English, TOEFL/IELTS score is to be submitted with the application for admission:

TOEFL Score (Test dates must be within 2 years or less from the date of application):

          ≥ 563 (paper-based)

          ≥ 223 (computer-based)

          ≥ 85 (internet-based)

IELTS Score (Test date must be within 2 years or less from the date of application):

          ≥ 6.0

Applicants without TOEFL/IELTS would still be eligible to apply, but they may be subjected to an interview/test if deemed necessary by the School.

Programme Structure

There are two options of study, one with coursework and dissertation, and the other with coursework only. Each course is of 3 AUs, and consists of 39 hours of lectures. Candidates who undertake a project of 6 AUs must submit a dissertation on it.

Option 1

Coursework + Dissertation

Option 2

Coursework Only

8 Courses + Dissertation Project

(30 AUs in total)

10 Courses

(30 AUs in total)

4 specialized electives (≥ 12 AUs)

4 specialized electives ((≥ 12 AUs)

4 general electives (≤ 12 AUs)

6 general electives (≤ 18 AUs)

Dissertation (6 AUs)


Full-time students are strongly recommended to select the dissertation option, however this option is recommended only for students with a high level of English proficiency. Students taking the dissertation option may take a longer time to complete the programme.

Note:  The programme structure will be subject to change without prior notice. 



Both full-time and part-time programmes are offered (unless stated). Part-time candidates are expected to obtain permission from their employer before admission to the programme. All classes are conducted in the evenings, while examinations are conducted during office hours.

Type of Coursework Programme

Minimum Candidature

Maximum Candidature

Master of Science

(Full Time)

1 year 3 year

Master of Science

(Part Time)

2 year 4 year


Programme Calendar

Semester 1 August to December
Semester 2 January to May
Week 1 to 14 Lecture (Inclusive of 1-week recess)
Week 15 to 17 Examinations
Other  Vacation


Graduate courses offered by Master of Science (MSc) Communications Engineering:

Specialized Elective Courses (Students are required to take a min of 4 out of all the 5 specialized elective courses)

Course Code Course Title Course Content AUs
EE6101  DIGITAL COMMUNICATION SYSTEMS  Communication signals and baseband transmission. Digital modulation/demodulation. Error correction coding. Spread-spectrum techniques. 3
EE6108  COMPUTER NETWORKS  Network protocols and services. Transport protocols and services. Local area networks. Wide area networks and internetworking. Broadband and Asynchronous Transfer Mode (ATM) networks. 3
EE6122  OPTICAL FIBRE COMMUNICATIONS  Optical fibre fundamentals. System components. Optical fibre transmission systems. WDM systems and subsystems. Optical networks. Measurement techniques. 3
EE6128  RF CIRCUITS FOR WIRELESS COMMUNICATIONS  Microstrip Line and Network Parameters. Microwave Power Dividers and couplers. Microwave Filters. Amplifiers. Oscillators and Synthesizers. Detectors and Mixers. Frequency Multipliers and Control Circuits. RF Receiver Design. 3
EE6129  WIRELESS & MOBILE RADIO SYSTEMS  Wireless channel models. Fading and ISI mitigation techniques. Cellular concept and Multiple access techniques. Satellite communications. 3

General Elective Courses

Course Code Course Title Course Content AUs
EE6010  PROJECT MANAGEMENT & TECHNOPRENEURSHIP  Project Initiation and Planning. Project Scheduling and Implementation. Project Monitoring, Control and Evaluation. Innovation and Entrepreneurship. 3
EE6102  CYBER SECURITY & BLOCKCHAIN TECHNOLOGY  Cyber Security Threat Landscape, Industry 4.0 and Cyber Security, Cyber Security Education, Awareness and Compliance, Cyber Security Planning, Policies and Compliance, Cyber Security Risk Assessments and Biometric-based Security approaches, Public key Infrastructure (PKI), Web Security and role of firewalls and Intrusion Detection, Online Payment, and Cryptocurrencies. Basics of Blockchain technology, Types of blockchain Technology, Blockchain Technology Applications for Industry 4.0, use cases and real-world case studies 3
EE6130  ANTENNAS & PROPAGATION FOR WIRELESS SYSTEMS  Review of EM Theory and Basic Antenna Parameters. Wire and Aperture Antennas. Planar Antenna and Antenna Arrays. Small Antennas and Antenna Measurements. Principles of Radio Wave Propagation. Ground Wave and Ionospehric Propagation. Mobile Communication Channel.  3
EE6223  COMPUTER CONTROL NETWORKS  Data Networks in Control and Automation. Local Area Network Concepts and Fieldbus. Application Layer of Fieldbus and MAP. Internetworking and Protocols. Real-time Operating Systems and Distributed Control. Network Performance and Planning. Multimedia in Advanced Control and Instrumentation. 3
EE6227  GENETIC ALGORITHMS & MACHINE LEARNING  Review of Combinatorics and Probability. Introduction of Genetic Algorithms. Differential Evolution. Particle Swarm Optimization. Advanced Techniques. Principles of Machine Learning. Paradigms of Machine Learning. Kernel Methods. 3
EE6285  COMPUTATIONAL INTELLIGENCE  Introduction to Fuzzy Logic, Introduction to Fuzzy Sets, Introduction to Fuzzy Inference Systems, Fuzzy Logic Applications, Introduction to Genetic Algorithm, Fundamental Concepts of Artificial Neural Networks and Neural Network Architectures, Neural Network Applications 3
EE6301  SMART BIOSENSORS & SYSTEMS FOR HEALTHCARE  Introduction to biosensors and healthcare; Optical biosensors-fundamentals; Optical biosensors-applications; Biomedical imaging with optical technologies; Introduction to electrical biosensors- fundamentals; Introduction to electrical biosensors- fabrications; Applications of electrical biosensor; Introduction to bio-intelligent systems; Artificial intelligence in medical sensing and imaging 3
EE6303  ELECTROMAGNETIC COMPATIBILITY DESIGN  EMC Regulatory Requirements. Non-Ideal Behaviors of Passive Components. Conducted EMI and Filter Design. Electromagnetic Shielding. Basic Grounding Concept. Crosstalk. Printed Circuit Board Layout and Radiated EMI. Electrostatic Discharge. Radio Frequency Interference. Emission and Susceptibility Measurement Methods. 3
EE6341  ADVANCED ANALOG CIRCUITS  Low Noise Circuits, Wide-Bandwidth Amplifiers, Power Amplifiers, Active Filters, DC-DC Converters 3
EE6401  ADVANCED DIGITAL SIGNAL PROCESSING  Discrete-time signal analysis and filter design. Multi-rate digital signal processing. Linear prediction and optimal linear filters. Power spectrum estimation.  3
EE6403  DISTRIBUTED MULTIMEDIA SYSTEMS  Discrete signal analysis and digital filters. Power spectrum
estimation. Linear prediction and optimal linear filters. Multi-rate digital signal processing. DSP Architectures and applications.
EE6405  NATURAL LANGUAGE PROCESSING  Traditional: Bag-of-words, Preprocessing, Term weighting scheme, Feature extraction,. Topic modeling , ML classifiers and clustering methods, Evaluation Metrics, Word Embeddings
Deep Neural Networks: Graph convolutional network, Seq2Seq, Attention mechanism, Transformers and self-attention, Pretrained Language Models, Fine-tuning (hyper-parameter tuning), Applications (chatbot, machine translation, sentiment analysis, summarisation, classification, generation, auto-complete)
EE6427  VIDEO SIGNAL PROCESSING  Image and Video Basics. Image and Video Transform Coding. Filtering and Error Resilience for Image and Video. Image and Video Coding Principles and Standards. Recent and Emerging Topics in Image and Video Processing. 3
EE6483  ARTIFICIAL INTELLIGENCE & DATA MINING  Structures and Strategies for State Space Representation & Search. Heuristic Search. Data Mining Concepts and Algorithms. Classification and Prediction methods. Unsupervised Learning and Clustering Analysis. 3
EE6497  PATTERN RECOGNITION & DEEP LEARNING  Introduction, probability review, Bayesian Inference, Mixture Models and EM Algorithm, Markov Models and Hidden Markov Models, Sampling, Markov chain Monte Carlo (MCMC), Neural Networks, Deep Learning (CNN, RNN), Training Deep Networks, Deep Network Architectures, Applications, Generative Models, Self-supervised Learning. 3
EE7205  RESEARCH METHODS  Research Preparation and Planning. Research Sources and Review. Quantitative Methods for Data Analysis. Experimental research methods. Academic Writing & Presentation 3
EE7401  PROBABILITY & RANDOM PROCESSES  Probability concepts. Random variables. Multiple random variables. Sum of random variables and multidimensional distributions. Random Sequences. Probability density function estimation. Random variable simulation. Random processes. Correlation functions. Spectral density. Random processes 3
EE7402  STATISTICAL SIGNAL PROCESSING  Signal Estimation Theory. Properties of Estimators. Sequential estimation methods. Fundamentals of Detection Theory. Detection of Deterministic and Random Signals. 3
EE7403  IMAGE ANALYSIS & PATTERN RECOGNITION  Image Fundamentals. Image Enhancement and Restoration. Image Analysis. Decision Theory and Statistical Estimation. Classification and Clustering. Dimensionality Reduction. 3
EE6008  COLLABORATIVE RESEARCH & DEVELOPMENT PROJECT  Project Charter, Design and prototype development, Project implementation, Testing and instrumentation, Project report, Oral presentation, Demonstration 3

Note: the above curriculum is subject to change.

Tuition Fees

Five MSc programmes (Communications Engineering, Computer Control & Automation, Electronics, Power Engineering and Signal Processing) are self-financed programmes. 

Students of these programmes are not eligible for Service Obligation/ MOE Subsidies

The tuition fees per module (3 AUs) and per dissertation (6 AUs) for admission from AY2020 onwards are shown in the table as follows:

Singaporeans (SC) Singapore PRs (SPR) International Students (IS)
Per Module Per Dissertation^ Per Module Per Dissertation^ Per Module Per Dissertation^
S$3,270* S$6,540* S$3,815* S$7,630* S$4,360* S$8,720*
Minimum Total Programme Fee Minimum Total Programme Fee Minimum Total Programme Fee
S$32,700* S$38,150* S$43,600*

*Inclusive of 9% GST from 1 Jan 2024.

^The tuition fee for the Dissertation (6 AUs) will be twice of each module fee.

All fees listed above are in Singapore dollars (S$) and subject to annual revision by the school. The tuition fee is exclusive of living expenses and miscellaneous student fees.

The deposit fee of S$2,000 is payable upon acceptance of the offer and is non-refundable. It will be deducted from the full tuition fee.

Important Updates:

Below table for intakes starting from August 2024.

Per Course: S$4,883.20* Per Dissertation^: S$9,766.40*
Minimum Total Tuition Fees: S$48,832*
SC/SPR Incentive
All Singapore Citizens (SC) and Singapore Permanent Residents (SPR) will be eligible to receive a S$5,000 subsidy, and S$10,000 for needy SC/SPR students.

NTU Alumni Incentive
All NTU Alumni will receive 10% study incentives in the form of reduction in fees.

*Inclusive of 9% GST from 1 Jan 2024.
A Goods and Services Tax (GST) of 9% is levied on the import of goods, as well as nearly all supplies of goods and services in Singapore starting 1 Jan 2024.

A deposit fee of S$5,000 (from August 2024's intake onward) is payable upon acceptance of the offer and is non-refundable. It will be deducted from the full tuition fee.



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