Digital Communication

The course gives a fundamental introduction to the principles and systems for digital transmission of information over channels with Gaussian noise, including basic transmission and reception strategies, as well as an understanding of expected performance and performance limits. Through project work, the course gives the student skills in simulation of and experimentation with real transmitter and receiver hardware, as well as experimentation planning and reporting. The couse topics are: - Linear baseband digital (PAM) modulation, - upconversion and linear (QAM) and nonlinear (FSK) passband digital modulation, - Maximum a-Posteriori and Maximum Likelihood detection, non-coherent detection, - transmissiond bandwidth, Nyquist pulses, sampling and intersymbol interference, - Gaussian noise, and related error analysis in symbol detection, - Gaussian channel capacity, coding, convolutional codes, decoding, and error analysis, - signal space, signal constellations, equivalent baseband model, and - tradeoffs between energy, data rate and error rate.

Knowledge: The candidate has: - understanding of digitally modulated signals and their properties, - deep understanding of the detection principles for digital signals, - good understanding of error behavior and performance of digital receivers - understanding of central abstraction methods and models used to describe digital transmission methods - good overview of performance limits. Skills: The candidate can: - design and parametrize digital transmitters and corresponding receivers, - characterize the central qualities and performance of digital transmission through simulation and analysis, - find tradeoffs between energy, bandwidth, and error rate, - evaluate performance limits, and - evaluate system performance with simulations.

Lectures and integrated exercises. Project work in groups, with supervision.