Dynamic Spectrum Access Decisions. George F. Elmasry

Dynamic Spectrum Access Decisions - George F. Elmasry


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and 8-ary PSK."/> Schematic illustration of the decisions zones for 8-ary PSK. Schematic illustration of the PDF contour of a PSK signal and perpendicular bisector between two symbols in signal space. Schematic illustration of the hypothesizing the presence of noise and interfering signal with PSK signals.

      Equations (3.15)–(3.18) and Figure 3.6 explain an overlay concept of the noise, in‐band signal, and interfering signal. If the noise floor estimation is accurate, the sensor can subtract w(n) from Equations (3.11)(3.14). If the sensor has information regarding the transmission power of the in‐band signal, the distance to the emitter and terrain information, then s(n) can be estimated, allowing the sensor to hypothesize the presence of an interfering signal in a close to optimal way.16

      It is critical to understand the importance of collecting large samples by the spectrum sensor to make the ROC model viable in implementation. More importantly, noise and the interfering signal are manifested not by a simple increase in energy detection level, but by an increase in the variance of the collected samples. Relying on a small sample can lead to suboptimal results as the set of small samples can be misleading. Estimating the deviation in the energy samples is what accurately reflects the impact of noise and interfering signals and what should be used for dynamically adapting the thresholds.

      The ROC model implementation at the sensing node could be the first step towards making spectrum sensing decisions. The next step is referred to as decision fusion (DF), which uses the ROC model hypotheses outcome to make more comprehensive spectrum sensing decisions. This section presents local, distributed, and centralized decision fusion approaches to help the reader decide the most suitable place to make a DSA decision in a hybrid DSA system.

      3.3.1 Local Decision Fusion

      Notice that if the local fusion process stops without further fusion of spectrum sensing information, the higher


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