But may not be sufficient for another since the

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but may not be sufficient for another since the transmitters might be employing different signal power levels or the transmission ranges may vary altogether. Since Simulink only supports baseband modulation, we will need to implement all of the signals at baseband as well. We will now conduct a series of ten trials across a range of SNR values. For each trial: 1. Compute the probability of false alarm (the number of times we incorrectly say that there is a signal present, when in fact there isn’t). 2. Compute the probability of missed detection (the number of times we did not find the signal). 3. What threshold values did you employ in your energy detection implementations? Which modulation scheme is most often detected? Which modulation scheme is most often not detected? 2.3 Understanding Cyclostationary Detectors Finally, let us examine the spectral coherence of the three signals generated. The spectral coherence is a measure of the correlation between each cyclic frequency and ranges in magnitude from 0 to 1. High coherence terms indicate some periodicity within the signal being examined. Reset the parameters of each channel in datagen.mdl to the following: SNR: 100 dB β : 0.5 Run the model and open cyclic.m , and use the following lines of code for the QPSK (qpsk), FSK (fsk), and PSK (psk) signals: 10
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[SCF Cx] = cyclic(qpsk); Cxplot = surf(abs(Cx)); set(Cxplot, ’edgecolor’,’interp’); Using this code, answer the following questions: 1. Generate an AWGN vector and plot its coherence. Does this plot support the conclusion that cyclic detectors are robust to Gaussian noise? Why? 2. Why might cyclic detectors be susceptible to frequency selective fading? 3. Adjust the roll-off factors of the pulse shaping filters and re-examine the coherence functions. What effect does the excess bandwidth have on the effectiveness of the detector? 11
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3 GNU Radio Experimentation In the previous lab, you learned how to create your own hierarchical blocks in GRC. Although useful, you are still limited to working with the existing GRC blocks. There are times when you need greater flexibility and you want to write your own, fully custom blocks in Python or C++ code. In this section of the lab, you will learn how to create custom GNU Radio blocks and import them into GRC. As you create your own blocks, you will undoubtedly need to refer to the GNU Radio documentation, so we begin this section with an introduction to the GNU Radio documentation. 3.1 Introduction to Doxygen Doxygen is a tool that scans through source code and automatically generates documentation (typi- cally HTML pages) for the code. In addition to source code comments, Doxygen extracts the names of functions, classes, constants, variables, etc., and creates hyperlinks between the source files. This makes it very convenient to browse through source code.
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