Channel equalization for chaotic communications systems

Many communications systems based on chaotic systems have recently been proposed, including chaotic modulation, masking, and spread spectrum. However, most of the proposed algorithms disregard the distortions introduced by communication channels, and fail to work in realistic communications scenarios. Channel equalization algorithms specifically designed for chaotic communications systems are needed to remove the distortions.; In this thesis, channel equalization algorithms for chaotic communications systems are developed. These algorithms exploit information specific to chaotic systems to undo channel distortions. First, a novel equalization algorithm is presented for chaotic systems with linear time-invariant representations. This algorithm incorporates the linear time-invariant representation of chaotic system in the receiver design to equalize channel distortions. Secondly, optimal estimation and sequential channel equalization algorithms based on the Viterbi algorithm are developed for chaotic systems with symbolic dynamics representations. The symbolic dynamics representations of these chaotic systems enable representations based on trellis diagrams Then, the Viterbi algorithm is used to estimate and equalize the transmitted chaotic sequences. Next, using the principles of turbo processing, a lower complexity, iterative equalization algorithm for chaotic communications systems is presented where channel equalization and chaotic demodulation are performed jointly and iteratively. Finally, a multiuser chaotic communications scheme is presented with accompanying multiuser estimation and channel equalization algorithms. The multiuser chaotic system is first represented with an extended trellis diagram by combining the trellis diagrams for the individual chaotic systems. Then, the Viterbi algorithm is used to both remove the distortions introduced by the communication channel and separate the individual chaotic sequences.