There are two main categories of data compression. Lossless compression involves transmitting all of the data in the original signal but using fewer bits. Lossy compression, on the other hand, allows for some reduction in the quality of the transmitted signal.

Obviously there has to be some limit on the loss in quality, depending on the application. For instance, up until now the expectation of voice quality has been less for a mobile telephone than for a wireline telephone.

This expectation is now changing as wireless telephones become more common. People are no longer impressed with the fact that wireless telephony works at all; they want it to work as well as a fixed telephone.

Lossless compression schemes generally look for redundancies in the data. For instance, a string of zeros can be replaced with a code that tells the receiver the length of the string. This technique is called run-length encoding.

It is very useful in some applications: facsimile (fax) transmission, for instance, where it is unnecessary to transmit as much data for white space on the paper as for the message. In voice transmission it is possible to greatly reduce the bit rate, or even stop transmitting altogether, during time periods in which there is no speech.

For example, during a typical conversation each person generally talks for less than half the time. Taking advantage of this to increase the bandwidth for transmission in real time requires there to be more than one signal multiplexed.

When the technique is applied to a radio system, it also allows battery-powered transmitters to conserve power by shutting off or reducing power during pauses in speech.

Lossy compression can involve reducing the number of bits per sample or reducing the sampling rate. As we have seen, the first reduces the signal-to-noise ratio and the second limits the high-frequency response of the signal, so there are limits to both methods.

Other lossy compression methods rely on knowledge of the type of signal, and often, on knowledge of
human perception. This means that voice, music, and video signals would have to be treated differently.

These more advanced methods often involve the need for quite extensive digital signal processing. Because of this, they have only recently become practical for real-time use with portable equipment. A couple of brief examples will show the sort of thing that is possible.

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