| Summary: | Consider a receiver that has an unknown impulse response in the form of linear time-invariant system, which is driven by an input signal and random noise with an unknown distribution. If the unknown impulse response of the receiver could be identified, then its equivalent frequency response can be used for calibration, using deconvolution aiming to regain the original signal under measurement. Hence, the estimation of the transfer function of the receiver is of great importance from both theoretical and practical applications. This thesis is devoted to the identification of the receiver’s unknown finite impulse response (FIR form), by observing only the output signal through it. More specifically, not only the amplitude and phase but also the orders of the finite impulse response of the receiver are unknown. A blind algorithm is tested for the identification of the unknown communication channel of the receiver in simulation. Further, in a practical implementation performed in this thesis such blind algorithm is combined with a technique to compute the receiver’s transfer functions. The word blind indicates that there is no restriction in the input signal set, it is allowed to be non-stationary with unknown statistical model, and hence this algorithm is particularly suitable for de-reverberation technology. The implementation of the blind algorithm is demonstrated through the Matlab simulation, and verified through experimental measurements, where several of the impairments of hardware will be considered in the analysis.
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