Every device that transmits power wirelessly must be approved by the FCC. All transmissions from cellphones, radios, and microwaves are carefully regulated, but so are unintentional transmissions from appliances such as light bulbs and refrigerators. Tight regulation is necessary because wireless spectrum is a notoriously scarce resource and an unlicensed transmission can disrupt the operation of every other radio device in the vicinity. As such, the FCC has divvied up the spectrum and sold licenses for frequency bands covering almost 8 orders of magnitude between 6 kHz and 300 GHz, and every year the range of frequencies that require a license increases. [1]
The recent increase in wireless technology has further compounded the problem of spectrum scarcity. As cellphone standards mature, their peak data-rates have steadily increased, requiring more and more spectrum bandwidth. In crowded metropolitan areas such as New York, San Francisco, and Washington D.C. there is often not enough bandwidth to go around.
Federal regulation aside, measurements and a close inspection of the wireless spectrum reveal a different picture. Many licensed bands see only occasional use, or are left empty all together, while other nearby bands are crowded beyond capacity. FCC reports on spectrum utilization reveal that even in the most densely packed urban areas the overall spectrum utilization rarely passes 35% at any one time. [2] The inefficient allocation of finite spectrum resources has created artificial scarcity where none need exist.
Current research into cognitive radios hopes to improve spectral utilization by allowing users from crowded bands to bleed off into nearby empty bands. In an ideal scenario a spectrum aware cognitive radio is able to sense the local spectrum usage and adapt its own radio parameters accordingly. As an example, consider a personal Wi-Fi network in a crowded New York apartment complex. The number of co-located networks present can easily fill the 2.4 GHz band, in which personal Wi-Fi devices are designed to operate. [1,2] Instead of adding an additional device to an over-used band, a cognitive radio would be able to sense the over-use of the allocated Wi-Fi spectrum and the underutilization of other nearby spectrum blocks. Once so determined the cognitive radio would operate in the free spectrum, thus more efficiently utilizing the total available spectrum. [3,4] Examples of spectrum blocks that may be underutilized may include empty broadcast television/radio stations, radio- astronomy blocks, radio-navigation blocks, and others. [2] The advance of cognitive radio and spectrum sensing radios is a high priority for the FCC. The 802.22 draft standard, which is still under review, is the FCC's first foray into cognitive radio and demonstrates their commitment and active interest in this emerging technology. [5]
Despite promise of cognitive radio, there are still many technical hurdles to overcome before the technology is ready to be implemented in a real world scenario. Among the many challenges that have yet to be solved, two of the more insidious are hidden primary users and spread spectrum primary users, both of which lead a cognitive radio to incorrectly decide that a spectrum block is empty, leading to signals that interfere with the licensed primary user. [6] The geometry of the hidden primary user problem is depicted in Fig. 1. Consider primary transmitter A, primary receiver B, and secondary user C who would like to use the spectrum licensed for use by A and B. Before operating C measures the energy in the band and compares it to a threshold set by background noise so as to determine if the band is in use. In the case where the secondary user C is just out of range of the primary transmitter A it may conclude that there is no primary user in the immediate vicinity and co-opt the spectrum. The problem arises when secondary user C begins to transmit. Although C is far away from A, the primary receiver B may be near enough to A to receive its signal. However, once C begins to transmit interference may obstruct those transmissions preventing the licensed spectrum usage between A and B. [6] Spread spectrum primary can be an equally insidious problem. Consider the frequency utilization plot depicted in Fig. 2 which is representative of a spread spectrum user. As in Fig. 2 a spread spectrum user may only require a very low power signal spread across a wide bandwidth. In the worst case scenario a cognitive radio system might test the spectrum in bands much smaller than the wide bandwidth used by the primary user. Unfortunately, the primary user's low power transmission is often designed to look like background noise, and may be interpreted as such by the cognitive radio. In fact the only way to distinguish a spread spectrum transmission from the background is to sample the entire bandwidth, which may be impossible for the cognitive radio, thus leading to false identification of empty spectrum. [6]
These problems must be overcome before it is possible to implement a fully cognitive radio system. Fortunately there are solutions to these and other problems including but not limited to better sensing hardware or central databases of current primary users. Once these technical and system-level hurdles have been overcome cognitive radio promises to greatly increase the bandwidth available to many applications by increasing the efficient utilization of previously allocated frequency bands.
© Doug Adams. The author grants permission to copy, distribute and display this work in unaltered form, with attribution to the author, for noncommercial purposes only. All other rights, including commercial rights, are reserved to the author.
[1] "United States Frequency Allocations: The Radio Spectrum," U.S. Depatment of Commerce, National Telecommunications and Information Administration, August 2011.
[2] "Notice of Proposed Rule Making and Order, FCC 03-322, in the Matter of Facilitating Opportunities for Flexible, Efficient, and Reliable Spectrum Use Employing Cognitive Radio Technologies," U.S. Federal Communications Commission, FCC-03-322A1, December 2003.
[3] N. Savage, "10 Emerging Technologies: Cognitive Radio," Technology Review, 1 Mar 06.
[4] G. Staple and K. Werbach, "The End of Spectrum Scarcity," IEEE Spectrum, 1 Mar 04.
[5] C. Cordeiro, K. Challapali and D. Birru, "802.22: An Introduction to the First Wireless Standard Based on Cognitive Radios," J. Commun. 1, 38 (2006).
[6] T. Yucek and H. Arslan, "A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications," IEEE Commun. Surveys and Tutorials 11, 116 (2009).