Iterative equalization for chaotic communications systems

Many previously proposed communications systems based on chaos disregard common channel distortions and fail to work under realistic channel conditions. A sequential equalization algorithm based on the Viterbi algorithm has shown good performance to combat channel distortions. However, the amount of computation needed for the sequential equalization algorithm increases sequentially with the number of channel parameters and the precision of the estimated chaotic sequence. A lower complexity, iterative equalization algorithm for chaotic communication systems is developed. The trellis size is greatly reduced by implementing the channel equalization and chaotic demodulation separately, but connecting them iteratively. The proposed algorithms are simulated under both time-invariant and time-varying channel distortions. Bit-error rate graphs are illustrated for each case.