Homework 9
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Reading
- Chapter 2 in the Anderson text
Problems
- Sketch the optimum MAP receiver implementation using a bank of
filters matched to the basis of signal space
.
- Sketch the optimum ML receiver implementation using a bank of
correlators that multiply by the signal space basis functions
.
- Sketch the optimum MAP receiver implementation using a bank of
correlators that multiply by the pulses
.
- Sketch the optimum ML receiver implementation using a bank of
filters matched to the pulses
.
- Sketch the generalized transmitter that inputs bits on one end
and synthesizes the signal pulse
- What is a decision region?
- How do MAP and ML decision regions differ?
- Let
and
be two symbols in a binary
communication system occurring with probabilities
and
. Which symbol will have a larger decision
region if the ML decision rule is used? Which symbol will have a
larger decision region if the MAP rule is used?
- Under what condition does the MAP and ML rules lead to the same
decision?
- Was the signal space development worth it? The answer is:
``Yes, definitely!'' Why is working with the signal space
representation of
, and 
easier than working
with the waveforms themselves?
- The ML decision rule can be explained as a minimum distance rule
and as a maximum correlation rule. How is this possible?
- Calculate the average symbol energy and average bit energy of
the five constellations in Figure 2.26 (page 51 of the Anderson
text).
Copyright 2008,
by the Contributing Authors.
Cite/attribute Resource.
admin. (2006, June 29). Homework 9. Retrieved November 24, 2009, from Free Online Course Materials — USU OpenCourseWare Web site: http://ocw.usu.edu/Electrical_and_Computer_Engineering/Communication_Systems_I_1/hw9.html.
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