Blind MMSE Equalizer for Nonlinear SIMO Systems
Abdulmajid Lawal, Karim Abed‐Meraim, Qadri Mayyala, Navid Iqbal, Azzedine Zerguine · 2021
This work presents a novel minimum mean squared error (MMSE) equalizer for blind signal estimation of a nonlinear single input multiple outputs (SIMO) system. The zero and τ delay MMSE equalizer parameters are blindly estimated using the property that they belong to both the signal subspace and the kernel of a properly truncated data covariance matrix. Moreover, in the proposed approach, an appropriate demixing technique is employed to get rid of the inherent ambiguity to the equalized signal in such a nonlinear context. Numerical simulations show that the proposed MMSE blind SIMO nonlinear estimation exhibits a promising performance at a relatively low computational cost.