Visualizing the error bitstream as 2-D image develops a qualitative feel for the impact of bit error rate on the
data output of a binary communication system. That is, what value of BER corresponds to a "high quality" image transmission?
Or, what value of BER makes the received image "poor quality"?
View the Figure 5 screencast video to learn how to reshape the error bitstream
into a two-dimensional array suitable for display as a binary (2-level) image using the LabVIEW subVIs "Flatten Pixmap" and
"Draw Flattened Pixmap." In addition, learn how to programmatically control the size of the front-panel image indicator
using a "property node." Modify your application VI accordingly to produce SystemFour.vi.
Experiment with SystemFour.vi to study the relationship between BER and image size. To begin,
set the bitstream length to 1,024 to produce a 32x32 image. Set the bit error rate to 0.0001. Describe the appearance of the
error bitstream as an image, and state the relative "quality" of the image (remember that an ideal error image would always be
uniformly black).
Now, gradually increase the bitstream length to 200,000 while watching the image. Would you still consider the image to be at
the same quality level as before? What BER value do you need to obtain the same quality level you stated for the short bitstream
length?
Explain why a specific BER value can be considered acceptable for some types of transmitted messages and not for others.
"Starting point collection that gathers all modules from this course"
"In this project, develop a simple model for a transmitter, channel, and receiver, and study the performance of the system in terms of bit error rate (BER). Channel errors are visualized as images […]"