Research Article
Implementation of a Reconfiguration Algorithm for Cognitive Radio
@INPROCEEDINGS{10.1109/CROWNCOM.2007.4549792, author={Troy Weingart and Gary V. Yee and Douglas C. Sicker and Dirk Grunwald}, title={Implementation of a Reconfiguration Algorithm for Cognitive Radio}, proceedings={2nd International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications}, publisher={IEEE}, proceedings_a={CROWNCOM}, year={2008}, month={6}, keywords={Application software Chromium Cognitive radio Communication system software Computer architecture Hardware Interference Measurement Radio frequency Wireless communication}, doi={10.1109/CROWNCOM.2007.4549792} }- Troy Weingart
Gary V. Yee
Douglas C. Sicker
Dirk Grunwald
Year: 2008
Implementation of a Reconfiguration Algorithm for Cognitive Radio
CROWNCOM
IEEE
DOI: 10.1109/CROWNCOM.2007.4549792
Abstract
In wireless communication systems, advances in computer architecture and processor technology have made it possible for functionality previously implemented in hardware to become tunable via software. These software-defined radios (SDRs) will allow new radio devices to sense, reason, and adapt to changes in the RF environment and/or application requirements making them cognitive radios (CRs). Fully exploiting the flexibility of cognitive radios, however, requires an understanding of how different permutations of radio parameters impact application-specific performance metrics. For example, a CR that is not meeting its bit loss goals could change its operating frequency to reduce the impact of interference. However, the added overhead from changing frequencies could result in an application failing its latency requirements. This paper describes one such method for configuring a cognitive radio and demonstrates the efficacy of the technique on both a simulation based analysis and an in situ evaluation on a software radio platform. Our reconfiguration system quantifies the influence of radio parameters such as frequency agility, bit rate, and transmit power for adapting communication at the application, medium access control, and physical layers. The method calls for exhaustively evaluating a set of CR configurations against a variety of performance metrics and applying statistical processes to determine which settings will have the most significant impact on performance. Once this is done, the experimental results are then used to inform the design of an algorithm that is able to reconfigure to meet performance goals.
