Thursday, January 16, 2014

Spectrum Policy is Approaching a Revolution

Ever since the publishing of the U.S. National Broadband Plan in 2010, innovations in spectrum management have been at the forefront of thinking about the future of communications in the U.S. market.

In the United States, about half of all spectrum most suitable for communications, fixed and mobile, is licensed to various Federal government agencies, and, as you might well expect, much of that spectrum arguably is inefficiently managed.

Much of the new thinking centers on fundamental changes in the process whereby spectrum is made available for communications uses.

As a practical matter, though there are several ways to wring more effective use out of a finite spectrum resource, the absolute amount of spectrum useful for communications is limited.


As demand continues to grow, we bump up against physical constraints, even if demand shaping (Wi-Fi offload, tariffs), better technology (signal compression, better algorithms, agile frequency hopping) and network design (small cells, carrier Wi-Fi) can have meaningful impact.

Still, making better use of existing spectrum is among the tools policymakers can wield.

The President’s Council of Advisors on Science and Technology (PCAST) report makes a couple of nearly-revolutionary statements. Among the observations is the impractical method traditionally used to reclaim and then commercialize spectrum (“clear and auction”), simply because the costs of transition are so high.


The other really-novel insight is the observation that assigning spectrum in slivers, each with an assigned application profile, is inefficient, in light of modern technology.

In the wireless and mobile communications business, spectrum exhaust is a perennial problem. But there is new thinking that perhaps such scarcity is perhaps partly a result of allocation policies, not an absolute “shortage” of spectrum as such.


No comments:

Will AI Actually Boost Productivity and Consumer Demand? Maybe Not

A recent report by PwC suggests artificial intelligence will generate $15.7 trillion in economic impact to 2030. Most of us, reading, seein...