DIGITAL COMMUNICATIONS
UNIT-2
Introduction:- The purpose of a communication system is to carry information bearing signals (base band signals) from one place to another over a communication channel. One might have known that this has been achieved by the use of various modulation techniques.
What do we mean by Information? To answer this question we need to invoke “Information theory”, Information theory is a branch of probability theory which may be applied to the study of the communication systems. This broadly based Mathematical discipline has made fundamental contributions not only to communications, but also to computer science, statistical physics, statistical inference and probability and statistics.
In the context of communications, Information theory deals with Mathematical modelling and analysis of communication system rather than with physical sources and physical channels.
Information Theory provides answers to two questions
- What is the irreducible complexity below which a signal cannot be compared?
- What is the ultimate transmission rate for reliable communication over a noisy channel?
The answers to these questions lie in the
- Entropy of a source
- Capacity of a channel.
Entropy is defined in terms of the probabilistic behaviour of a source of information.
Capacity is defined as the intrinsic ability of a channel to convey information. It is generally related to the noise characteristic of the channel.
A remarkable result that emerges from information theory is
Entropy of source H(x) < Channel capacity C this means that error free communication over the channel can be achieved.
We begin our study of information theory by discussing the relationships among Uncertainty, Information and Entropy. One can also learn about self & Mutual Information.