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.