Communication Theory

Communications theory is the basis for understanding how information can be transmitted
over physical channels. The main focus will be on digital communication. Stochastic
processes are covered to characterize signals that are not fully known. Examples are speech,
video signals, and unwanted signals like noise and interference. Digital formatting is
needed to process and transmit signals digitally, and we therefore discuss sampling and
quantization. The next step is to find ways of inserting digital information into analog
channels. Examples of physical channels are introduced. Nyquist theory helps us find
the maximum density of discrete signals that can be transmitted over a channel with given
bandwidth and Shannon theory reveals how many bits can be transmitted per channel use.
Different modulation methods are introduced for converting information to signals for
transmission. Receiver noise and optimal detection of different modulations in noise
are treated. Modulation methods are evaluated through bit error rate, energy efficiency
and spectral efficiency.

The course goals are to make the students able to (knowledge:)
a) understand theoretical channel capacity limits for physical channels,
b) understand the correspondence between received signal quality and channel resources,
c) master certain methods for information transmission for digital systems,
(general qualifications:)
master mathematical and statistical methods combined with programming for developing algorithms for practical communication problems,
(general qualifications:)
a) collaborate to solve complex problems,
b) read and apply scientific literature in the field.

Lectures and exercises. If there is a re-examination, the examination form may be changed from written to oral.