A chaos tracker applied to non-coherent detection in chaos-based digital communication systems

In chaos-based communication systems, parameter variation in the chaos generator and additive channel noise represent two practical problems that are hard to solve. For chaos-based digital communication, non-coherent detection has the advantage that the receiver does not need to reproduce the same chaos basis function that has been generated in the transmitter. Such reproduction typically requires a fragile operation of chaos synchronisation between the transmitter and the receiver. In this paper, we consider non-coherent detection under the practical condition of the transmitted signal being contaminated by noise and its generating function being subject to strong parameter variation. A novel tracker is proposed for reconstructing the transmitted chaotic signal. This tracker uses a modified radial-basis-function (RBF) neural network which incorporates a learning algorithm for tracking the noisy chaotic signal under parameter variation. Using this tracker, a non-coherent detector is designed for demodulating chaos-shift-keying (CSK) signals in a CSK digital communication system. Computer simulations, in which the Chua´s circuit is used as the chaos generator, are presented to demonstrate the tracking ability and CSK demodulation of the proposed method