An Introduction to Information Theory
An Introduction to Information Theory. Instructor: Prof. Adrish Banerjee, Department of Electrical Engineering, IIT Kanpur. Information Theory answers two fundamental questions: what is the maximum data rate at which we can transmit over a communication link, and what is the fundamental limit of data compression. In this course we will explore answers to these two questions. We will study some practical source compression algorithms. We will also study how to compute channel capacity of simple channels. (from nptel.ac.in)
| Lecture 19 - Gaussian Channel |
We first describe a Gaussian channel and compute its capacity under power constraint. We then prove the rate achievability for the Gaussian channel with a power constraint P and noise variance N. Next we prove converse to the coding theorem for Gaussian channel. Finally, we derive expression for channel capacity for bandlimited additive white Gaussian noise channel.
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