Semi-Blind Stochastic Maximum Likelihood For Frequency Selective MIMO Channels

Abstract:
We propose a semi-blind Stochastic Maximum Likelihood (SML) estimator for frequency selective Multi-Input Multi-Output (MIMO) channel. To resolve the optimization problem we use the Expectation-Maximization (EM) algorithm. We first propose a Hidden Markov Model (HMM) for the MIMO frequency selective channel which gives us a formulation of the EM algorithm by introducing forward and backward parameters. Previously, semi-blind SML methods were provided for time-multiplexed pilot and data symbols. In this work, the semi-blind SML is proposed for the embedded pilot scheme which is attractive for its spectral efficiency. We also compare the semi-blind SML for the embedded pilot scheme with the blind SML and show the benefit of using semi-blind SML over blind SML.