CSPA

Communication Signal Processing and Algorithms (TE61003)

In this course, we consider two fundamental problems in statistical signal processing---detection and estimation---and their applications in digital communications. The first part of the course introduces statistical decision theory, techniques in hypothesis testing, and their performance analysis. The second part of the course deals with parameter estimation theory. For both deterministic and random parameters, we present various optimal estimators and investigate their properties. Various applications of detection and estimation theory will be introduced in the class. Examples include multiuser detection, channel estimation, iterative decoding, and distributed detection and estimation.

Course Material