Wireless Signal Processing

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Fukawa Kazuhiko 
Lecture2  Exercise0  Experiment0
Syllabus updated
Lecture notes updated
Fall Semester

Outline of lecture

The lecture focuses on applications of signal processing to wireless digital communications, such
as equalization, adaptive array antennas, and interference cancellation. In addition, adaptive algorithms, which estimate parameters of these items, are detailed.

Purpose of lecture

A major aim of the lecture is to help students gain a deep understanding of important transmission techniques for wireless digital communications.

Plan of lecture

1. Introduction and Review of Basic Knowledge
2. Signal Models for Wireless Communications
3. Statistics of Fading Channels
4. Wiener Filters and Least-Mean-Square (LMS) Algorithm
5. Recursive Least-Squares (RLS) Algorithm
6. Kalman Filters
7. Channel Equalization
8. Blind Deconvolution
9. Frequency-Domain Equalization
10. Turbo Principle
11. Diversity Combining and Adaptive Array Antennas
12. Nonlinear Interference Cancellation
13. MIMO Signal Detection
14. Precoding Techniques
15. Final Examination

Textbook and reference

Materials will be prepared by the lecturer.

Related and/or prerequisite courses

Basic communication engineering course and signal processing course are prerequisite.


Marks are based on examinations and reports.

Comments from lecturer

Any students who fully understand the lecture will not feel difficulty in following state-of-the-art techniques for wireless digital communications.

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