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WiMax Operator's Manual

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CHAPTER 7 ■ SERVICE DEPLOYMENTS OVER PUBLIC WIRELESS MANS 169<br />

puts one in a position of trading capacity off against presentation quality. Moreover, heavily<br />

compressed signals are highly intolerant of data loss because they have already been robbed of<br />

the redundancy to compensate for it. Compression buys the network operator something, but,<br />

as the saying goes, there is no free lunch.<br />

Compression is a vast subject, much too vast to treat with any thoroughness here, but<br />

most compression techniques fall into a few basic categories. The simplest seek to remove<br />

redundant information in a signal and only register changes from one sample to the next. More<br />

sophisticated techniques use what are known as codecs, which are idealized models appropriate<br />

to a given type of information such as representations of the human voice or a physical<br />

depiction of the human form. The information that is to be conveyed is compared to the<br />

model, and only what is unique to the individual message is transmitted. Still other compression<br />

techniques are based on underlying regularities in the forms of the entities depicted in the<br />

data or on perceptual codecs, where features that ordinarily would go unnoticed by a human<br />

observer will not be transmitted. Whatever the individual compression technique, all such<br />

techniques fit into two overarching categories: lossless compression and lossy compression. In<br />

the former, the original message can be reconstructed perfectly even though not all the information<br />

in it is actually transmitted, and in lossless transmission a recognizable facsimile is<br />

created at the receive end that does not contain all of the original information.<br />

The widely used MPEG compression schemes for audio and video are good examples of<br />

lossy compression depending upon perceptual codecs. They produce perfectly recognizable<br />

sounds and images, but, depending on the compression ratio (that is, the ratio of data removed<br />

to data preserved), they may degrade image and sound quality. The compression techniques in<br />

common use for audio and video today have grown very sophisticated, and at moderate compression<br />

ratios (say, five to one), they are well nigh undetectable by most viewers and listeners.<br />

And, inasmuch as this is true, they leverage existing bandwidth effectively. A telephone call<br />

that would require 64Kbps can be made with 8 or even 4 kilobits with little loss of fidelity. A<br />

high-definition television signal with several times the information per frame as a traditional<br />

National Television Standard Committee (NTSC) analog signal can yet be squeezed into a<br />

6MHz NTSC channel while yielding a much more detailed image.<br />

Compression is built into many Web tools used today such as real-time video and audio<br />

players and is not generally used as an overall strategy on the part of the network operator,<br />

though numerous product offerings are available for that purpose. The problem with using<br />

them is that they have to be enabled in every customer terminal that is to receive a compressed<br />

signal, so the logistics of using compression tends to be challenging. Nevertheless, I expect<br />

compression to assume greater importance over time.<br />

The routing protocol used end to end will also have a considerable bearing on latency<br />

and jitter and hence on QoS. Again, this will primarily concern the operator or operators of<br />

the backbone, not the metro operator. Frequently, a message will pass through more than<br />

one long-haul network in traversing a great distance. Unfortunately, since many long-haul<br />

operators jealously guard routing information within their own networks and do not make it<br />

available to other network operators, a router in one network attempting to plot a route across<br />

intervening networks to a final destination may simply lack the information to make optimal<br />

choices with predictably unfortunate consequences in regard to QoS. To some extent servicelevel<br />

agreements between and among long-haul providers can obviate such difficulties, but<br />

often the party seeking to maintain QoS by this means will have to pay dearly to do so.<br />

Finally, I should mention the methods for supporting QoS that use proprietary route analysis<br />

techniques but do not depend on special arrangements with long-haul service providers.

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