  We investigate a turbo soft detector based on the expectation propagation
(EP) algorithm for large-scale multiple-input multiple-output (MIMO) systems.
Optimal detection in MIMO systems becomes computationally unfeasible for
high-order modulations and/or large number of antennas. In this situation, the
linear minimum mean square error (LMMSE) exhibits a low-complexity with a good
performance, however far from optimal. To improve the performance, the EP
algorithm can be used. In this paper, we review previous EP-based detectors and
enhance their estimation in terms of complexity and performance. Specifically,
we improve the convergence of the self-iterated EP stage by replacing the
uniform prior by a non-uniform one, which better characterizes the information
returned by the decoder once the turbo procedure starts. We also review the EP
parameters to avoid instabilities when using high-order modulations and to
reduce the computational complexity. Simulation results illustrate the
robustness and enhanced performance of this novel detector in comparison with
previous approaches found in the literature. Results also show that the
proposed detector is robust in the presence of imperfect channel state
information (CSI).
