Blind multidimensional matched filtering techniques for single input multiple output communications

In this paper, blind multidimensional matched filtering techniques for Single Input Multiple Output (SIMO) communications are examined. To improve the signal-to-noise ratio prior to the equalization process, three different techniques are proposed to blindly implement the multidimensional matched filtering. Different from the blind channel identification techniques for SIMO channels in the literature, the proposed techniques require neither the implementation inefficient matrix decomposition methods nor the higher-order statistics of the received data. Therefore, they are favorable over existing methods due to their simplicity in application. The matched filter equivalents are established through the use of an adaptive filter as well as the channel equalization being performed blindly. It has been shown that the equalization performance of the proposed methods are close to the matched filter bound, and to support this, a comparison between the matched filter estimation error performances of our proposed techniques is also provided. A short discussion to improve the convergence speed of the proposed approaches is also included in this paper