Increasing the accuracy of nonlinear channel equalizers using multikernel method

Abstract

In previous articles, we proposed single kernel and multikernel equalizers for nonlinear satellite channels with significant improvements in performance. The results demonstrated that the advantages of kernel equalizers over radius basis function neural equalizers are the ability to achieve overall convergence, which results in smaller output errors. However, the limitation of single kernel equalizers is that the output errors are still quite large. Multikernel equalizers can overcome this disadvantage but the calculation is quite complex. To simplify the computation, this paper proposes a multikernel equalizer based on Online Multi-Kernel Normal LMS, MKNLMS, algorithm.