Semi-blind Mutually Referenced Equalizers for a Nonlinear Signal Estimation
Abdulmajid Lawal, Karim Abed‐Meraim, Azzedine Zerguine, Ali Hussein Muqaibel · 2023
In digital communication, nonlinearity is a frequent source of signal and channel distortion. Such distortions often need equalization techniques or devices to correct them. An equalization technique for recovering nonlinear multichannel signals in convolutive mixture is presented in this article. The proposed work uses the mutually referenced equalization technique to estimate the equalizer and the transmitted signal from the nonlinear convolutive mixture while in the present of quadratic nonlinearities. The proposed semi-blind model builds a cost function that offers an equalization solution by combining data, pilots, and the mutually referenced equalizer approach. The proposed method offers a number of benefits, including ease of implementation, resistance against channel order misspecification, and the ability to provide several equalization delays with a single solution. The simulation findings demonstrate that the proposed approach has fascinating performance characteristics and is resilient to low SNR.