A Correlation-Less Approach Towards Adaptive Channel Equalizer Based on Wiener–Hopf Equation

Abstract

Wiener, the well-known adaptive filter is seen in almost all the applications of adaptive signal processing. It gets the weight updating by solving the Wiener –Hopf equation (ωopt = R−1P). When implemented on the state of the art hardware, like ACIS or FPGA, this filter results in substantial resource consumption. This paper proposes updating the filter weights by reducing the need for an auto-correlation matrix (R) and calculating the filter weights based on cross-correlation vector (P) only. This approach would result in a noticeable resource reduction by compromising some of the performance that may be acceptable in voice or video being less sensitive. The proposed correlation-less approach and the conventional method are first simulated in Matlab and then is implemented in Xilinx Vertex 7 FPGA for one to one comparison. The results indicate that the proposed approach reduces a significant amount of resources along with acceptable performance characteristics. Therefore, it may be incorporated in various applications of mobile communication, especially the adaptive channel equalizer.