Wireless Communications

The course introduces the following contents: the overview of wireless communications systems; the characteristics of wireless propagation channels and their descriptions, including large and small scale of fading channels and their features in the time and frequency domains, and the spatial-time channel model of the multi-antenna systems; the wireless channel capacity and the adaptive modulation and coding including the capacity limits of the wireless channels under the possessing of various channel state information and the impact on the selection of modulation and coding schemes. Then two very representative wireless physical layer techniques are introduced including the Orthogonal Frequency Division Multiplexing (OFDM) and the Multi-Input Multi-Output (MIMO) techniques. Their design conceptions, key issues and solution ideas are discussed. After that, the wireless communications systems are generalized from single-user to multi-user scenario, and the capacity, the user scheduling and recourses allocation of a multi-user system are discussed. Then the practical issues of a wireless communications system is introduced including the hardware structure of a transceiver, the idea of the software defined radio (SDR), etc. Finally, the 3GPP long-term evolution (LTE) standard, as the 4th generation of the wireless communications system, is taken as an example, to discuss the practical considerations of the realization of a wireless communication system.

Signal Detection and Estimation

The theory of signal detection and estimation is an important branch of modern information theory. Using theories of probability and mathematical statistics as tools, it forms a discipline integrating system theory and communications engineering. It is a technology studying how to discover, identify, measure, and extract the useful signal coexisting with noise and interferences. Signal detection and estimation technologies have been widely applied in wireless communications, wireline communications, radar, and even radio astronomy, seismology, biological physics, and medical science, and this course is one of the most important course for the major in Information and Communications Engineering. Through this course, students can have a comprehensive and systematic understanding of signal detection and estimation theory, grasp the fundamental approach for receiver design and performance analyses via statistical inference theory, and learn state-of-the-art detection techniques in wireless communications systems.

Theory and Applications of Communication Networks

This is a theoretical course on the fundamentals of data communication networks. Much of the course will focus on analysis and evaluation of the transmission process and performance of each network layers, based on the development of the queueing theory, information theory and probability theory, etc. Students who take the course will be benefited in both their future researches and gaining emerging technologies, in fields of information technology and communication engineering. Topics discussed will include: queueing theory, layered network architecture, models of the data link layer, network layer and transport layer with performance analysis and network routing design.

The Principles of Passive and Active Microwave Circuits

Focusing on the design of microwave circuits and components, this course offers an introduction to the fundamental concepts necessary for design. The course made up of three parts: The first part is about microwave concepts based on fundamental principles of microwave engineering, which include the electromagnetic theory, transmission line theory, waveguides and microwave network analysis; the second part presents the contents of passive microwave circuits including the impedance matching, microwave resonators, power dividers, directional couplers and microwave filters; and the third part offers the active microwave circuits, which covers noise and nonlinear effects in microwave circuits, detectors and FET mixers, pin diode control circuits, the design of microwave amplifiers and oscillators. Graduate students will be required to practice on computers with computer-aided design (CAD) software for microwave circuit analysis, S-parameters measurement for microwave components with vector network analyzer in experimental time. And there is assignment after each lecture.

Vector Quantization and Image Processing

In this course, digital communication system will be briefly introduced first. Then, the principle and architecture of vector quantization algorithm, the performance evaluation method of a vector quantization system, the codebook generation method by Linde–Buzo– Gray training, the fast codeword search method by vector features or test inequality, the index assignment method by annealing will be discussed in detail. Finally, the application possibilities of vector quantization algorithm in content-based image retrieval, digital image watermarking, and hyperspectral data compression will also be explored. And in the end, the promising future work in the field of vector quantization algorithm research will be discussed.