Master of Engineering

HCMUT has started master programs since 1990. The Division provide full-time and part-time Master of Enginnering program major in Telecommunication Engineering.

 Candidates have to pass the entrance examination organized yearly by the Postgraduate Study Office and possess an English competency equivalent to TOEFL ITP 400 or IELTS 4.5. They are selected according to the annual intake targeted at 1000 students.

 The curriculum is 1.5-2 years with the total required credits of 36-50. To qualify for the degree of Master of Engineering in addition to English level of TOEIC 550, a student has to accumulate sufficient required credits following coursework or research-work programs and successfully defend a thesis evaluated by a professional scientific committee.

 Graduates are expected to possess strong specialized knowledge, practical skills and adaptation with continuous development in sciences and technology in order to solve specific issues in their majors.

Quality of Service (QoS) is becoming an increasingly important factor in the evolving networks. Efficient approaches for QoS support would lead to effective management of IP network resources to provide higher levels of quality, performance, control, and security. Nowadays, QoS technologies need to be deployed in not only fixed networks but also wireless networks according to the multi-services requirements and heterogeneous network environments. This course addresses the various IP QoS technologies and how to implement those QoS technologies in the current heterogeneous IP networks. Besides, queuing theory is also provided for the students to model several QoS parameters of networks. Several advanced topics on simulating network QoS are provided to verify the given theoretical background.

The course provides foundational and advanced knowledge on most updated topics on image and audio processing: audio coding and compression, audio recognition and synthesis, image analysis, image and video enhancement, superresolution, image and video compression, multi-view video processing.

The subject is dedicated to the analysis and simulation of a single lossy or lossless connection, which provide its responses in frequency and time domains. The coupling or parasitic effects within data bus lines are also studied, where the equivalent models for loose or tight couplings are to be presented. The subject is realised with short final projects of simulations using Matlab or professional circuit simulators such as SPICE, CIRCUITMAKER,…

This course provides fundamental knowledge of information theory such as entropy, mutual information, entropy rates of a stochastic process, data compression, channel capacity, Gaussian channel, and rate distortion theory.

The course is intended to provide solid knowledge on encoding, decoding, performance analysis, and applications of channel codes from the fundamental such as linear block codes, convolutional codes, Turbo codes, LDPC codes to the advanced such as BICM code, RA code, Raptor code, LT code, Online code, …

This course provides advanced microwave theories and techniques for the analysis, design, simulation, fabrication and measurement of passive and active circuits constituting modern microwave systems for wireless communications and radar. Microwave circuits presented in this course include Power Dividers/Combiners, Couplers, Hybrids, Isolators and Circulators, Filters, Detectors, Low noise Amplifier, Power Amplifier, Broadband Amplifier, Oscillator and Mixer. The course also presents the effects of noise and nonlinearity distortion on the microwave system performance from which the system design of microwave transceivers is conducted. Simulators such as ADS, Cadence and SONET, and microwave equipments such as network analyzer, spectrum analyzer, synthesizer and noise figure analyzer are introduced as well with the objective of providing students necessary skills for working in the microwave engineering field. The course projects for design, simulation and fabrication of microwave circuits help students verify the theory from experiment. The students are evaluated through homeworks, quizzes, project and the final exam.

The goal of this course is to provide students a deep understanding of the background of the wireless sensor networking field and practical applications of the technology. The course content focuses on modern, robust systems and networking architecture for integrating ubiquitous instrumentation of the physical world with leading-edge IP. It emphasizes the use of open standards at several levels - including popular embedded operating systems (e.g. TinyOS and Contiki OS), IEEE 802.15.4 radio, 6LoWPAN adaptation, IPv6 networking, routing, and configuration, UDP/TCP transport, HTTP, REST/SOAP application layers – as they apply to ubiquitous embedded network devices and applications. Moreover, labs and demos provide in-depth hands-on experience in the application of core concepts using a wireless sensor network kernel on modern microcontrollers

The couse describes the cryptography issues including symmetric ciphers, asymmetric ciphers, integrity, key distribution, and authentication. Moreover, the course also deals with the practive of network security including TLS/SSL, 802.11, SSH, IPSEC.

This course focuses on the fundamentals of optimization methods, and their applications in digital signal processing and wireless communications. The topics include unconstrained and constrained optimization, linear and quadratic programming, Lagrange theory, interior-point methods, convex optimization and semi-definite programming. Algorithmic methods introduced in the class include gradient methods, Newton's method, conjugate direction methods, and interior-point methods. The topics of engineering applications include filter designs, pattern classification, blind image separation in signal processing; and estimation, detection, equalizers, beamforming, resource allocations in wireless communications.

• Provide background knowledge on MMIC and RFIC technologies.
• Provide solid knowledge on analysis and design of RF/microwave tranceivers for wireless communications.
• Provide comprehensive knowledge on analysis, design, simulation, layout, fabrication and measurement of CMOS RF/Microwave integrated circuits including low noise amplifiers, mixers, oscillators and power amplifiers.
• Provide skills of using simulation softwares such as Cadence, ADS and SONET, and microwave equiments such as vector network analyzer, spectrum analyzer, synthesizer and noise figure analyzer.

• To provide a comprehensive knowledge on Digital Communications based on the stochastic process of signals in single path and multipath communications.
• The contents are included the concepts of signal representations in signal spaces and understanding in deep characteristics of signals then how to treat and improve the quality of digital communications through noisy channels.
• A project accompanied to the course will be recommended and implemented hardwares (if applicable) to help students improve knowledge on both theory and practical applications.

This course introduces the fundamental and practical aspects of optical network technology, architecture, design and analysis techniques. Optical hardware technologies are illustrated and characterized as fundamental network building blocks on which optical transmission systems and network architectures are based. Topics include review of the basic properties of light propagation in optical fibers; basic and advanced fiber types and theirs applications; operation and applications of laser diodes and LEDs; principles of various laser types such as multi-longitude mode laser, single longitude mode laser, tunable laser and mode-locked laser; principles of direct detection and coherent detection optical receivers; principles of fiber grating, optical multiplexer, optical switches, optical modulators and optical amplifiers; design considerations and analysis of single wavelength optical link for both analog and digital signals; operation of wavelength division multiplexing fiber-optic communication systems.

The course is intended to provide updated-and-solid knowledge on wireless communications: path-loss and shadowing, wireless channel models, adaptive modulation and coding, diversity techniques, equalizers, multi-carrier modulation, and MIMO signal processing.

The course provides the knowledge in deep of the computer network from the transmission to the application layers. The course is not intended to include the physical layer. Concretely, the course provides knowledge of the data-link layer (Ethernet, frame relay), network layer (routing protocols, routing algorithms), transport layer (transport protocols, congestion control algorithms, flow control algorithms), and the application layer (DNS, web, FTP, email, monitoring).

The course provides updated-and-solid knowledge on digital image processing and multimedia: image processing systems, digital image principles, mathematic principles on image transforms, selected methods on image analysis, selected methods on image processing, image morphology, multimedia.

• To provide a comprehensive knowledge on Advanced Digital Signal Processing for graduate levels. It can be also a signal processing background applied to other courses.
• The contents are included the concepts of analog and digital signal processing; the design methods for Finite-Impulse response (FIR) and Infinite Impulse response (IIR) digital filters based on the window method and bilinear transformation.
• The processing of nonstationary signals by time-frequency and time-scale analysis are addressed to be the advanced level for signal processing.
• A project accompanied to the course will be recommended to the hardware implementation with the DSP family TMS320Cxxxx for signal processing or system analysis.

The characteristics of stochastic process and basic stochastic processes applied in electronics and communications engineering are reviewed. The methods of stochastic signal processing; such as the linear optimum filtering (Wiener filter, linear prediction, Kalman filter), the linear adaptive filtering (least-mean-square and recursive least-squares algorithms), the estimation theory, and the spectrum estimation; are considered. The applications of stochastic signal processing in communications engineering; such as linear prediction and adaptive linear prediction, system identification, channel equalization and adaptive channel equalization, smart antennas and interference cancellation problem, estimation of signal parameters, and frequency estimation and direction – of – arrival estimation; are also presented.   

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