Cognitive Radio:A Solution to Wireless Jamming

Cognitive Radio:To avoid future wireless traffic jams, Heather “Haitao” Zheng is finding ways to exploit unused radio spectrum.It’s a local effect — within 30 to 60 meters of a transceiver — but there’s just no more space in the part of the radio spectrum designated for Wi-Fi.
Imagine, then, what happens as more devices go wireless — not just laptops, or cell phones and BlackBerrys, but sensor networks that monitor everything from temperature in office buildings to moisture in cornfields, radio frequency ID tags that track merchandise at the local Wal-Mart, devices that monitor nursing-home patients. All these gadgets have to share a finite — and increasingly crowded — amount of radio spectrum.
Heather Zheng, an assistant professor of computer science at the University of California, Santa Barbara, is working on ways to allow wireless devices to more efficiently share the airwaves. The problem, she says, is not a dearth of radio spectrum; it’s the way that spectrum is used.
The Federal Communications Commission in the United States, and its counterparts around the world, allocate the radio spectrum in swaths of frequency of varying widths. One band covers AM radio, another VHF television, still others cell phones, citizen’s-band radio, pagers, and so on; now, just as wireless devices have begun proliferating, there’s little left over to dole out.
But as anyone who has twirled a radio dial knows, not every channel in every band is always in use. In fact, the FCC has determined that, in some locations or at some times of day, 70 percent of the allocated spectrum may be sitting idle, even though it’s officially spoken for.
Zheng thinks the solution lies with cognitive radios, devices that figure out which frequencies are quiet and pick one or more over which to transmit and receive data. Without careful planning, however, certain bands could still end up jammed. Zheng’s answer is to teach cognitive radios to negotiate with other devices in their vicinity. In Zheng’s scheme, the FCC-designated owner of the spectrum gets priority, but other devices can divvy up unused spectrum among themselves.
But negotiation between devices uses bandwidth in itself, so Zheng simplified the process. She selected a set of rules based on “game theory” — a type of mathematical modeling often used to find the optimal solutions to economics problems — and designed software that made the devices follow those rules. Instead of each radio’s having to tell its neighbor what it’s doing, it simply observes its neighbors to see if they are transmitting and makes its own decisions.


Say hello to Cognitive Radio technology! The future of wireless!

Delivery of web content and video over next-generation wireless networks will require large amounts of bandwidth. The existing wireless spectrum in most countries, however, has already been fully allocated. Optimizing the use of this spectrum is therefore necessary to allow further development of wireless services.

One promising approach is called ’cognitive radio’, whereby a primary, licensed user and an unlicensed, secondary user share a wireless spectrum. However, adoption of this method has been hindered by the inability to avoid signal interference, which must be kept low. Now, Rui Zhang and Ying-Chang Liang, from the A*STAR Institute for InfoComm Research in Singapore and Feifei Gao, currently of Jacobs University in Germany, have proposed a practical and efficient scheme to determine and avoid interference on channels shared by multiple users1.

The team had previously proposed an approach for minimizing interference called ‘cognitive beamforming’. Under this scheme, a secondary radio uses multiple antennas—each transmitting at different powers—to modify its transmission parameters in a manner that avoids interference. However, this proposal required perfect and complete information about the primary radio and its channels to avoid interference, which made the scheme significantly less practical.

Under Zhang and co-workers’ new proposal, this stringent requirement is avoided because the secondary radio can ‘learn’ about the primary radio by periodically sampling its transmissions. The secondary radio can then numerically construct an ’effective interference channel’ that allows it to estimate the interference its transmissions would cause, and to alter them to minimize interference. The new proposal also allows for simultaneous primary and secondary transmissions at the same frequency, in contrast to other cognitive radio schemes.

Zhang and his co-workers also showed that a trade-off exists between the time the secondary radio spends learning to reducing the interference it causes, and the time it spends actually transmitting data. They calculated the optimum time spent at each activity, so as to maximize the secondary radio’s transmission speed.

The proposed scheme can be extended to multiple primary radio receivers and channels, and, while it has not yet been implemented, is potentially relevant to any wireless system that requires supporting two radio networks on a single frequency, according to Zhang. More generally, it “breaks the fundamental gridlock inherent to the conventional operation mode of cognitive radios,” says Zhang, “and the general cognitive beamforming approach on which it is based has already motivated considerable follow-up research.”