Abstract: An evaluation device is adapted for providing a transceiver system with performance information thereof. The transceiver system models a channel between a transmitter and a receiver thereof using Nakagami distribution with a fading parameter. The evaluation device includes a signal-to-noise ratio (SNR) computing module, a capacity computing module, and an output module. The SNR computing module is operable to set an average SNR for the channel between the transmitter and the receiver, and to compute an expected value and variance of an effective SNR of the transceiver system according to the fading parameter and the average SNR. The capacity computing module is operable to compute an outage capacity of the transceiver system based upon the expected value and the variance of the effective SNR and a transmission outage parameter. The output module is operable to provide the transceiver system with the average SNR and the outage capacity.

Abstract: An evaluation device is adapted for providing a transceiver system with performance information thereof. The transceiver system models a channel between a transmitter and a receiver thereof using Nakagami distribution with a fading parameter. The evaluation device includes a threshold value computing module, a signal-to-noise ratio (SNR) setting module, a probability computing module, and an output module. The threshold value computing module is operable to compute a threshold value based upon a given capacity. The SNR setting module is operable to set an average SNR for the channel between the transmitter and the receiver of the transceiver system. The probability computing module is operable, based upon the fading parameter, the average SNR and the threshold value, to compute an outage probability of the transceiver system corresponding to the given capacity. The output module is operable to provide the transceiver system with the average SNR and the outage probability.

Abstract: A signal analyzer includes a sampling unit, a filter unit coupled to the sampling unit, a computing unit coupled to the filter unit, and an output unit coupled to the computing unit. The sampling unit is operable to sample a time domain signal from a target system according to a predetermined sampling frequency to obtain a sampling signal. The filter unit is configured to perform filter processing upon the sampling signal so as to filter out harmonic frequency components from the sampling signal, thereby obtaining a fundamental frequency signal having a plurality of sample points. The computing unit is operable to compute a signal parameter set for each of temporally adjacent pairs of the sample points of the fundamental frequency signal. The output unit is configured to output information about dynamic behavior of the target system based upon the signal parameter sets computed by the computing unit.

Abstract: A method for determining an optimum sampling frequency to be performed by a power analyzer includes the following computer-implemented steps: sampling a time domain signal to obtain a sampling signal according to a predetermined sampling frequency; obtaining two reference sampling signals using higher and lower sampling frequencies compared to the predetermined sampling frequency; transforming the sampling signal and the reference sampling signals to frequency domain signals; computing a sum-of-amplitudes for each of the three frequency domain signals; estimating a minimum sum-of-amplitudes value and a corresponding re-sampling frequency; obtaining a new reference sampling signal using the re-sampling frequency; transforming the new reference sampling signal to a frequency domain signal, and computing a sum-of-amplitudes therefor; and re-estimating the minimum sum-of-amplitudes value and the corresponding re-sampling frequency.

Abstract: A method for establishing a simulating signal suitable for estimating a complex exponential signal includes the following computer-implemented steps: sampling a time domain signal of a physical system to obtain a sampling signal; transforming the sampling signal to a frequency domain signal using Fast Fourier Transform; determining parameters of the frequency domain signal; establishing a simulating signal; establishing a target function which is a deviation of the simulating signal from the sampling signal; obtaining correcting factors; iterating the target function using a gradient method and the correcting factors to obtain three sets of iterated signal parameters; obtaining corrected parameters using quadratic interpolation; and using the corrected parameters to correct the simulating signal, and establishing an updated target function. The simulating signal can be used to estimate dynamic behavior of the physical system if the updated target function converges to a tolerable range.