System identification using chaos with application to equalization of a chaotic modulation system

In this brief, we considered the problem of blind identification of an autoregressive (AR) system driven by a chaotic signal. Because of the inherently deterministic nature of a chaotic signal, a new dynamic-based estimation approach called minimum phase space volume (MPSV) technique was applied to identify an AR system. It was shown that not only could this chaotic approach provide an accurate identification, but it was also more effective than the conventional statistic method in the sense that the chaotic approach had a smaller mean squares error (MSE), and it was so robust that it did not require an order determination procedure. In a chaotic modulation communication system, since the signal of transmission is modulated by a chaotic dynamical system, equalization of the transmitted signal through a communication channel is therefore a problem of system identification with a chaotic probing signal. It was observed that the equalization performance of the chaotic approach was superior to the conventional statistical method. This is another benefit for using chaos in a spread spectrum communication system