Short Course Description
Structure of Digital Communication systems. Hypothesis testing and decision rules: Minimum error probability criterion, maximum likelihood criterion, Bayes loss criterion, Neyman-Pearson criterion. Discrete-time multidimensional communication systems (vector channels). Continuous-time communication systems (waveform channels). Signal-space representation of finite-energy signals. The optimal receiver for known signals in additive white Gaussian noise (AWGN) channels, and colored additive Gaussian noise channels. Bit and symbol error probabilities and performance analysis of digital communication systems. Digital modulation techniques: PSK, FSK, MSK, CPM, orthogonal signals, simplex signals. Non-coherent communications. Introduction to information theory and channel capacity. Introduction to coding theory: Block codes, convolutional codes, coding gain analysis, the Viterbi algorithm.
Full syllabus will be available to registered students only
