Estimation of the parameters of the electric network signal, usually present in many audio and video recordings, is known to have several important forensic applications. In this paper, we consider the problem of estimating the base frequency and signal to noise ratio (SNR). Although the electric network signal is present via its base frequency and its integer multiplies, recent estimators in the literature focus on single-tone models. In this work, we offer a multitone harmonic model for the electric network signal. We use the Cramer-Rao bound for the frequency estimation problem and show that this approach can lead to a theoretical O(M³) factor improvement in the estimation accuracy, where M is the number of harmonics. We then derive the computationally efficient form of the maximum-likelihood estimator, applicable in the limit of large number of measurements. The problem of estimating the SNR of the signal is also discussed. Through extensive tests on real data and data sets reported in the current literature, the performance of the new estimators is evaluated. Results indeed show a significant gain compared to the single-tone model, and are better than previously reported estimators in the literature for moderate and high SNR values.

The simulation of a free-space optical (FSO) communication channel in the presence of strong turbulence typically requires the generation of channel states with a K or gamma-gamma distribution and a predefined autocorrelation function. In this paper, we propose a simple and effective simulator of the strong-turbulence FSO channel that addresses the influence of the temporal covariance effect. Specifically, the proposed simulator provides K and gamma-gamma distributed values with the exponential autocorrelation function and a prescribed correlation time. This simulator is based on the numerical solution of the first-order stochastic differential equation. The simulated channel states are generated by a simple discrete-time differential equation and the simulator performance is analyzed in the paper.

Free-space optical (FSO) communication may be severely influenced by the inevitable turbulence effect that results in channel gain fluctuations and fading. The objective of this paper is to provide a simple and effective simulator of the weak-turbulence FSO channel that emulates the influence of the temporal covariance effect. Specifically, the proposed model is based on lognormal distributed samples with a corresponding correlation time. The simulator is based on the solution of the first-order stochastic differential equation (SDE). The results of the provided SDE analysis reveal its efficacy for turbulent channel modeling.