Abstract-In RF receivers nonlinearities are inherent to analog processing. This is the result of strong signals presence close to the bandwidth of the signal of interest, or a power excess of this signal. Both cases greatly deteriorate the receiver bit-error-rate. Methods to compensate for nonlinearities consist in equalizing resulting intermodulation terms by predistortion or a subtraction mechanism. In this article, we propose a proof of concept for a novel technique to limit the harmful effects of nonlinearities. It consists in making a measure of intermodulation terms power, thanks to a cyclostationary sensing mechanism. And then, to dynamically adapt receivers parameters to make it works in a linear regime. We detail principles of that method and develop the theoretical analysis of detection. Thanks to simulations, we show that this method is reliable and allows a nonlinearity detection 16dB below the compression point. This work was conducted in the scope of high end radio such as professional mobile radios (PMR) receiver.

Abstract-This paper considers the problem of detecting a QPSK communication signal on carrier. We propose a method to perform the detection thanks to second order cyclostationarity theory. It is well known that for such a signal, there is no cyclic frequency multiple of the studied signal carrier frequency. Hence, the basic method of second order cyclic-moments energy measurement is unable to detect any energy directly linked to the signal carrier. In this article, we propose a novel criterion based on second order cyclic-moments that exploits the convergence speed of the cyclic autocorrelation function estimator. We show that for a modulated QPSK signal the cyclic-correlation converges to zero but not in the same way if the cyclic frequency is a multiple of the carrier frequency or not. We develop a statistical test and derive the asymptotic probability density function of the criterion to propose a detection threshold. System performance simulation results are then evaluated by Monte Carlo simulations and compared to the results of fourth order nonlinear transformation method.

In this article, a filter bank is coupled with a CFAR detector to guarantee an efficient frame detection in presence of Doppler shift. This work is realized in scope of the NEMOSENS project, which aims to produce autonomous underwater vehicles (AUVs) able to communicate and move in a network thanks to UA modems. Many adverse phenomenons occur in the context of underwater acoustic. Most harmful effects for underwater acoustic communication (UAC) are the multi-path nature of the environment, the Doppler spread and the noise variability. The proposed method reduces the number of lost frames and gives a rough estimate of delay and Doppler shift. The followed approach is supported by simulations with simplified hypotheses, but the interest of this approach is also shown in real sea experiments.

In this article, we propose a theoretical framework to derive the stochastic behavior of the cyclic autocorrelation power (CAP). This function is especially used in cyclostationaritybased spectrum sensing for its robustness to noise uncertainty and its low computational cost. We first express the theoretical probability density function (PDF) of the cyclic autocorrelation power-which proves to follow a central scaled (respectively noncentral) chi-square distribution if the received samples consist of additive Gaussian noise (respectively noise plus a cyclostationary signal). In order to verify the accuracy of the proposed theoretical derivation, simulation results are then provided in terms of detection and false alarm probabilities.