Blind source separation and equalization of multiple-input multiple-output FIR channels for chaotic communication systems

In the last two decades, various blind channel equalization algorithms for chaotic communications systems have been developed by exploiting properties peculiar to chaotic signals. Almost in all of these algorithms, however, the propagation channel is assumed to be a single-input single-output (SISO) system. As far as we know, there is no study for multiple-input multiple-output (MIMO) unknown channel case. In this study, we propose a blind MIMO finite impulse response (FIR) channel equalization algorithm for chaotic communication systems. In MIMO communication systems, in addition to intersymbol interference (ISI), multiuser interference (MUI) is an important factor that hinders the detector performance. To increase the detector performance and achieve reliable, high-speed communication, proposed MIMO FIR channel equalization algorithm overcomes both ISI and MUI. Also, an optimum fixed filter that minimizes the mean square error (MSE) between chaotic input signals and equalizer outputs is designed. Since there do not exists a method for comparison, the proposed method is compared to the optimum fixed filter. Computer simulations show that the proposed algorithm gives results very close to those of optimum fixed filter and is able to recover all channel inputs simultaneously.