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Teaching Digital Communications in a Wireless World: Who Needs Equations?

Abstract

Digital communication is traditionally taught by examining the temporal and spectral response and the bit error rate performance of a system in the presence of additive noise as only a set of analytical equations. This approach seems to provide little insight or motivation for the undergraduate student. Undergraduate courses in digital signal and image processing extensively utilize simulation as an adjunct to understanding, but digital communications seems to be a laggard. An undergraduate curriculum in digital communications has been developed that couples the traditional analytical approach with the simulation of the system for further design, analysis, insight and motivation.

Bit by Bit Communication

Digital communication systems convey information from a source or transmitter over a channel to a sink or receiver. Modern communication systems often do so in the presence of additive channel noise and mild to severe channel and system non-linearities which tend to corrupt the transmission. Traditionally examining the performance of a digital communication system as only a set of analytical expressions, even if noise and non-linearities can somehow be described adequately, seems to provide little insight or motivation for the undergraduate student.

The sea change in this material is the introduction within the last decade of channel noise and non-linearities in the analysis of digital communication systems for the undergraduate student. Prior to this time, analog and digital communication systems were presented by analytical equations without channel noise and non-linearities and with a supplemental hardware laboratory without significant variability1 (for example, jitter). An undergraduate curriculum in digital communications has been developed that couples the traditional analytical approach and text with the simulation of the system as interconnected models (tokens) for design and analysis.

One illustration of this concept is that the requisite analytical expressions provide a nearly automatic solution to the spectrum of a modulated signal, but are these spectra really what occurs? Another illustration is that the relative bit error rate (BER) performance of the simple single point sampler and the more complex matched filter or correlation receiver in baseband rectangular pulse amplitude modulation (PAM) with additive white Gaussian noise (AWGN) can be now be compared.

There is something rewarding for the undergraduate student in assembling a digital communication system from models, executing a simulation and then obtaining the spectrum of the signal or the comparative performance of receiver architectures in AWGN, all without benefit of the analytical solution or, for that matter, any equations at all. A digital communication system simulation allows its virtual construction to explore the what-ifs of design in the presence of channel noise and synchronization in

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Silage, D. (2006, June), Teaching Digital Communications In A Wireless World: Who Needs Equations? Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--281