A Double EP-Based Proposal for Turbo Equalization

Abstract

This letter deals with the application of the expectation propagation (EP) algorithm to turbo equalization. The EP has been successfully applied to obtain either a better approximation at the output of the equalizer or at the output of the channel decoder to better initialize the Gaussian prior used by the equalizer. In this letter we combine both trends to propose a novel double EP-based equalizer that is able to decrease the number of iterations needed, reducing the computational complexity to twice that of the linear MMSE. This novel equalizer is developed in three different implementations: a block design that exploits the whole vector of observations, a Wiener filter-type approach that just uses the observations within a predefined window and a Kalman smoothing filter-type approach that emulates the BCJR behavior. Finally, we include some experimental results to compare the three different implementations and to detail their improvements with respect to other EP-based proposals in the literature.

Meta Learning-Based MIMO Detectors: Design, Simulation, and Experimental Test

“…Detection performance can be further improved by adopting a turbo-detection scheme through iterative information exchange between the signal detector and the channel decoder [12]. Several turbo receivers that use EP-based detectors have been applied [12]- [14]. However, the convergence speed and stability of such iterative detectors rely heavily on the setting of a number of handcrafted tuning [19], [25], [26] have been studied over the last few years.…”