Novel SMC techniques for blind equalization of flat-fading MIMO channels

We investigate two novel blind receivers for joint channel estimation and data detection in flat-fading multiple-input multiple-output (MIMO) communication systems. Both schemes are based on the sequential Monte Carlo (SMC) methodology, also known as particle filtering, and attain asymptotically optimal performance, both in terms of channel estimation and data detection. The most salient feature of the new SMC receivers is that their computational complexity growth is polynomial in the number of input data streams, in contrast to the complexity of most previously proposed SMC algorithms for blind MIMO equalization, which increases exponentially with the number of input streams. We present simulation results to show that the reduction in complexity is attained with a negligible impact on performance.