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<p>We investigate the application of the <emph>Bayesian expectation-maximization</emph>  (BEM) technique to the design of <emph>soft-in soft-out</emph>  (SISO) detection algorithms for wireless communication systems operating over channels affected by parametric uncertainty. First, the BEM algorithm is described in detail and its relationship with the well-known <emph>expectation-maximization</emph>  (EM) technique is explained. Then, some of its applications are illustrated. In particular, the problems of SISO detection of spread spectrum, single-carrier and multicarrier space-time block coded signals are analyzed. Numerical results show that BEM-based detectors perform closely to the <emph>maximum likelihood</emph>  (ML) receivers endowed with perfect channel state information as long as channel variations are not too fast.</p

Soft-In Soft-Output Detection in the Presence of Parametric Uncertainty via the Bayesian EM Algorithm