Implementation of Spectrum Analysis Functionality for IQ-Signal.
Abstract: The spectrum analyzer is a standard tool used to measure signals in the frequency domain. Traditional spectrum analyzers are based on sweeping a local oscillator and using this to mix signals down to an intermediate frequency (IF) and, subsequently filter them with a filter of settable characteristics, called the Resolution Bandwidth (RBW). This is still the preferred method when the requirement on dynamic range of the signals being measured is large. However, this approach has the drawbacks of being relatively slow, not adaptive and flexible for some specific need and certain special measurement functionalities cannot be done due to the sweeping. Due to this, Ericsson production test development would like to perform software-based spectrum analysis on sampled In-phase and Quadrature (IQ) signals. In this thesis, the introduction of IQ-signals and synthetic spectrum analysis (SSA) are presented. The statistical properties of root mean-square (RMS) and sample detectors for standard spectrum analyzer are investigated. The effect of swept time on statistical properties of the RMS and sample detectors were investigated and the results are presented in this work. The results of swept time effect for sample detector show the change in the variance of the statistical properties when continuous wave (CW) and two-tone test signals were used, however, for bandlimited Gaussian test signal, the variance of the statistical properties is not changed. For RMS detector, the swept time using two-tone and Gaussian test signals show the change in the variance of the statistical properties. Whereas, for CW test signal the statistical properties result in shift from higher power distribution level to lower power distribution level with increase in sweep-time. The emulation of spectrum analysis functionalities (RBW, envelope detector and 0detectors) for IQ-signal has been implemented in MATLAB. The verification of the implemented functionalities has been done by investigating the statistical properties of RMS and sample detectors for SSA for various test signals. These were found to agree with standard spectrum analyzer results. Moreover, the comparison of spectral traces and statistical properties between implemented functionality and standard spectrum analyzer have done. The results are showing agreement with industrial standard spectrum analyzer results.
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