Dynamic Spectrum Access Decisions. George F. Elmasry
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Название: Dynamic Spectrum Access Decisions
Автор: George F. Elmasry
Издательство: John Wiley & Sons Limited
Жанр: Отраслевые издания
isbn: 9781119573791
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Figure 3A.4 An example of a ROC curve in the ROC space.
3A.2 The ROC Curve Classifications
The ROC space should be used only in certain areas. Figure 3A.5 shows different aspects of the ROC space as follows:
1 The poor performance area. This area should be avoided. The tradeoff can be replaced by a random process.
2 The random cutoff. This is the ROC curve associated with random decision making.
3 The use area where the tradeoff between false alarm and detection probabilities is acceptable.
4 The perfect curve where the probability of detection is always 1. Note that the vertical line should be the decision threshold line in this case.
Figure 3A.5 ROC space working areas and thresholds.
With the ROC space, a classifier that yields acceptable performance should lie in the area between the random ROC curve and the perfect ROC curve. Figure 3A.6 shows multiple classifiers in the ROC space where the top classifier would yield better performance than the bottom classifier.27
Figure 3A.6 Multiple classifier ROC cuves.
Comparing Figure 3A.6 to Figure 3.2 one can see how the DSA ROC space can be conceptualized and how different SNIR ratios create different classifiers. Figure 3.2 shows that a higher SNIR brings the ROC curve closer to the perfect curve and how decision thresholds can be decided as vertical lines where at a given SNIR, a probability of false alarm should be identified as acceptable, leading to a probability of detection.
Notice the importance of decision fusion. A ROC based decision (e.g., signal detection) can be per an RF neighbor or per an antenna sector. While this single ROC decision can seem insufficient because of the presence of false alarm probability, decision fusion from all the RF neighbors or from all the antenna sectors can yield a more accurate signal detection outcome. Distributed cooperative DSA decisions can further increase the decision accuracy and have a centralized arbitrator with a bird's eye view of the area of operation, and a collection of local and distributed decisions can further increase the accuracy of DSA decision making.
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