Removing Cyclostationary Properties in a Chaos-Based Communication System

Abstract

Chaotic signals are used in digital communications primarily in a bid to increase the security of transmissions. Moreover, second-order cyclostationary characteristics can easily be identified in chaotic signals used in communication systems. The detection of the cyclostationary properties in the transmitted signal decreases the security level for such systems. In this paper, we focus our attention on the eradication of cyclostationary properties present in chaotic signals, and to that end, we introduce a new method based on symbol period randomization to eliminate the spectral lines corresponding to the multiples of the baud rates. Finally, we compare our proposed method with another existing method in order to show the efficiency of ours in eliminating the cyclostationary properties.

Design and analysis of a spread‐spectrum communication system with chaos‐based variation of both phase‐coded carrier and spreading factor

“…To overcome this drawback, in this paper, the spreading factor is designed to vary in the communication process and this variation leads to the variation of bit duration and bit energy. The study in [50] proved that the variation of bit or symbol duration can remove the cyclostationary properties. Fig.…”

Cyclostationarity: New trends and applications

“…Ad hoc receivers and processors have been derived for: blind detection of long-code code-division multiple access (CDMA) signals [216], quadrature amplitude modulated (QAM) signal identification [82], blind recognition and detection of orthogonal frequency division multiplexing (OFDM) signals [41,320,363], detection of binary offset carrier (BOC) signals adopted in global navigation satellite systems (GNSSs) [306] and of other mobile satellite transmissions [80], discrimination of worldwide interoperability for microwave access (WiMax) versus ultra wide-band (UWB) signals [341], blind recognition of single carrier linearly digitally modulated (SCLD) and OFDM signals [333], detection of interleaved single carrier frequency division multiple access (SC-FDMA) signals [244], classification of space-time block codes [240], digital television signal detection [373], and design of chaos-based communications systems [180]. Other ad hoc receivers are presented in [4,22,87,179,181,243,260,263,288,304,326,368,370,375] for communication signals and in [215] for radar signals.…”

Application of order cyclostationary demodulation to damage detection in a direct-driven wind turbine bearing

“…The cyclostationary demodulation can be considered as an extension of the modulation frequency detector, where the amplitude and frequency demodulation information can be extracted. Because the unrelated noise components in the analyzed signal's autocorrelation for nonzero lag approach zero, the cyclostationary demodulation is ideally robust to noise [12]. The autocorrelation of an analyzed signal x (t) can be estimated as…”