Cognitive Radio: Technology Impact on Regulation--Introduction of Dynamic Policies

Alex Wanda
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Regulations based on static broadcast geometries cannot address the spatial, numeric, and spectral dynamics of future radio technology. Technologists must begin to address not only how to construct such new technologies, but also to address how to bring dynamics into the regulatory framework.

When spectrum management rules are dynamic with respect to frequency then the rules for particular spectrum-based services tend to differ based on where a device is authorized to operate in the RF spectrum. Cognitive radios can change frequency readily, in seconds or milliseconds. These devices must incorporate aspects of the governing rules or policies from each of the different spectral areas in which they might operate.

New devices that incorporate wireless fidelity with mobile telephones and “roam” between wide area networks (WANs) and local area networks (LANs) are examples of how multiple spectrum policies can be merged within a single device. The dynamics are quite limited, yet possible under government and industry policies. The capacity to adjust spectrum policies dynamically opens the new possibility of dynamic spectrum policies. These policies can be at the device level, by which operational envelopes can be downloaded and modified by either the regulatory agency or the primary license holder. The dynamic policies can also be at the system level, whereas the network policies that are used to optimize performance can now add the parameter of spectrum access and the associated policies for using a specific band, at a location, with the particular system load. Three operational dimensions of spectrum policy avail themselves to dynamics—specifically, time, space, and interference.



 Time: An example of using the time dynamics in spectrum policy was exhibited in the early days of radio. Particular AM stations would cease transmission late at night and resume early the next morning. Time-based dynamics can be extended significantly from this example. One extension is to include scheduled /expected interactions that are quite predictable. These may include secondary market transactions, in which a secondary provider accesses the spectrum using a separate network. These also may include the flexible access of a band by the primary user for a different application, such as reusing a cell site to provide data telemetry to/from vending machines. A further extension of this concept, which would be more opportunistic in character and less predictable, yet reliable for both primary and secondary users, may include using the spectrum for a short time or within a very limited area. One example is micro-transactions within the secondary market for such “spot” use. Another could be a non-cooperative use of spectrum that is currently not in use. The opportunistic use would exhibit quick transactions that could be impractical for human intervention.
 Space: Spatial dynamics are depicted in cases where the location of a device would determine its operational characteristics. One proposal for spatial dynamics includes the allowance of higher power transmission of unlicensed devices in rural environs. Another proposal is the use of unlicensed devices in bands where the device is sufficiently far away from a UHF TV transmitter. Location sensing would be necessary for the first proposal. Signal strength sensing would be necessary for the second proposal. In either case, because the transmitters are stationary, the location information is static. Therefore, once the boundaries are determined through calculation or measurement, then these boundaries could be programmed into a device. However, extending the concept to avoid mobile transmitters creates additional complexities. The distance to mobile transmitters would be constantly changing, and thus more automated sensing and interference avoidance techniques would be required.
 Interference: In contrast to the spatial and temporal dynamics, interference dynamics would need to understand not only its environment but also the impact of its own transmission on the surrounding environment. The capacity to accurately measure and model the environment would be needed. A significant amount of R&D has occurred over the past decade to improve the fidelity of simulation and modeling of RF propagation. Companies such as Remcom have products that are examples of those developments. Additionally, device technology has significantly reduced the cost of RF sensing while also improving in fidelity.

There are many specific applications of dynamic spectrum policies. In the case where dynamic policies overlay current static policies, the choice for the device designer is whether to provide those new capabilities at additional cost for each device. An example of this is the case of whether to use licensed spectrum, secondary market spectrum, or unlicensed devices. Licensed spectrum has an assured quality of spectrum access and interference but is associated with higher spectrum costs. Each of the other choices has less assurance of quality but at lower spectrum costs. It is easy to expect that with dynamic policies an explosion of new sensing devices and cooperative networks can be developed. These will be aimed at providing cost-effective solutions for both licensed and unlicensed uses. The incorporation of more processing capacity within licensed and unlicensed devices will present system developers with a large number of choices to provide new services with variable quality to the consumer.


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