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By Peter Coffee  |  Posted 2004-08-30 Print this article Print
 
 
 
 
 
 
 


A UWB approach violates all conventional notions of good radio engineering practice, using much more bandwidth than information theory requires for a given amount of content.

To put this in terms of nightscapes and flashlights, every UWB user has the same kind of white-light flashlight, but each is assigned a different distinctive timing pattern to use with a blinker switch—and is given a pair of glasses whose lenses can switch between being opaque or transparent, controlled by the same coded pattern.

At any given moment, a person will see glimpses of things that his or her communication partners didnt intend to illuminate, but, over time, that person will mostly see the targets that his or her own coded pattern is picking out. If other users or groups are idle, an active user will see a less confused signal or will be able to get a larger number of clear and distinct views over any given period of time.

As activity by other users increases, each user will be able to make an independent choice about trading bandwidth for quality. By settling for fewer independent views per unit of time, users will be able to use statistical techniques to elevate what they want to see above the noise. This phenomenon is called processing gain, in contrast to the amplification gain of a conventional volume control.

This is where UWB techniques start to defy common sense. A simple spreadsheet, using random-number formulas and a mix of logical and statistical functions, is all thats needed to demonstrate that a signal can be detected—at any desired accuracy level—even when that signal is actually weaker than the random noise of static and the other interfering signals in the same spectral band.

If the story stopped here, at the level of mathematics and information theory, then UWB proponents would therefore be justified in using phrases such as "spectrum glut"—as did the normally restrained international journal, The Economist, on its Aug. 14 cover. When the math meets the metal of actual radio hardware, though, things get much more complicated.

Strong nearby signals, for example, induce a behavior called front-end overload, which reduces the sensitivity of a radio receiver across its entire range. Moreover, some radio applications, such as radio astronomy, cant depend on Moores Law to make processing gain more affordable as channel activity grows; they have to detect the signals that they find.

An elevated noise floor, with ever-more users transmitting growing numbers of coded sequences, could drive astronomical users literally to the far side of the moon in search of a quiet radio shadow within which they could make their observations.

Freescales XS110 approval lets the UWB genie out of the bottle, even if the other messy contents of that bottle are so far being spilled only in the band between 3GHz and 10GHz—a spectral region of limited application because basic physics limit the range of signals in that band.

Powerful interests will almost certainly contend, however, that the benefits of UWB should be combined with the greater range and versatility of radio frequencies that are currently used by other established user communities. The contest that follows will be unlike any other in the history of technology—not a duel between alternative uses of a resource but one between essentially different ideas of what the resource is.

Technology Editor Peter Coffee can be reached at peter_coffee@ziffdavis.com.

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Peter Coffee is Director of Platform Research at salesforce.com, where he serves as a liaison with the developer community to define the opportunity and clarify developersÔÇÖ technical requirements on the companyÔÇÖs evolving Apex Platform. Peter previously spent 18 years with eWEEK (formerly PC Week), the national news magazine of enterprise technology practice, where he reviewed software development tools and methods and wrote regular columns on emerging technologies and professional community issues.Before he began writing full-time in 1989, Peter spent eleven years in technical and management positions at Exxon and The Aerospace Corporation, including management of the latter companyÔÇÖs first desktop computing planning team and applied research in applications of artificial intelligence techniques. He holds an engineering degree from MIT and an MBA from Pepperdine University, he has held teaching appointments in computer science, business analytics and information systems management at Pepperdine, UCLA, and Chapman College.
 
 
 
 
 
 
 

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