Section III
Communications is gradually converging into a single fiber optic and
wireless worldwide network for all types of communication. To
understand the problems in creating this network we need to
understand the concept of information from the perspective of
communication engineers. This concept enables communication engineers
to design communication networks with enough capacity to carry the
intended messages. It also provides a theory to obtain the maximum
compression of digital messages.
Shannon in 1949 developed a theory of communication based on a
measure of information which enables communication engineers to
determine the communication capacity required to communicate the
messages. In order to discuss Shannon's measure of the information
content in a message, consider the following simple diagram of a
communication system:
At the information source the input message is digitized and at the destination
the message is converted back into the input form, that is, text, voice, etc.
Noise will cause the output to differ from the input. To build a communication
system, we need to know the volume of the message. Intuitively, consider a fresh
water system in a city. To build this system you must know the size of pipe
to transmit the desired amount of water to each household. Since we have converted
the message into binary code, Shannon's contribution was to define the message
volume in bits.
To gain some intuitive understanding of his concept we need to
consider some examples. If you had to transmit an infinite string of
1's with no zero's, you can use the string's pattern to greatly
compress the number of bits you must transmit. In this case, once you
remove the pattern there is nothing left to transmit. Now suppose 0's
were placed at random intervals in the string of 1's. You would have
to transmit the pattern of all ones and also transmit the locations
of the zero's. The greater difficulty in transmitting the second
message over the first is directly related to the number of randomly
spaced 0's. Now consider a picture composed of a green field. To
transmit the message all you must transmit is the pattern. The video
message becomes progressively more difficult to transmit depending on
the number of blue dots randomly placed in the picture. The
Shannon information message is a measure of the randomness, or
entropy, of the message. Shannon's measure says nothing about the
meaning of the message. The communication engineer does not care
whether the message is nonsense syllables or national secrets.
Entropy, or randomness, refers to number of bits required to transmit
the random elements. Shannon is very important because he provided
communication engineers with a theory for designing appropriately
sized communication channels for transmitting the information content
of the messages. If the channel capacity is greater than the
information measure (entropy) of the message, it is theoretically
possible to transmit the message without error in a noisy channel. On
the crest and trough of every wave you can place a bit or no bit.
Thus to transmit a message the frequency of channel must be greater
than one half the number of bits which must be transmitted per
second.
Digital communications presents a fundamental problem in that the raw digitization
of analog messages greatly increases their size. One approach is to use a bigger
communication channel to transmit the digitized message. A better approach to
deal with raw digitized messages is to compress the message using compression
algorithms, which in the case of teleconferencing are called codices. For example,
a telephone conversation is digitized into 64,000 bits/sec. The entropy measure
of a voice message may be less than 1000 bits/sec. Communication engineers have
developed techniques to compress messages so that the amount of bits is closer
to the entropy measure. For example, telephone conversations can be transmitted
by voice recorder at 2400 baud, a term meaning bits per second. In order to
market inexpensive teleconferencing there are powerful incentives to compress
video messages. The current status is:
| Type |
Baud (transmission) Rate |
|
|---|---|---|
Slides |
1.2K - 56K |
|
Poor to medium quality motion |
56K - 1.2k |
|
Quality motion |
1.2M - 140M |
Check out various types of compression technology: