Physics-Aware Initialization Refinement in Code-Aided EM for Blind Channel Estimation

doi:10.1109/LSP.2026.3666849

Physics-Aware Initialization Refinement in Code-Aided EM for Blind Channel Estimation

2026-02-23

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DOI：10.1109/LSP.2026.3666849

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This paper addresses the well-known local maximum problem of the expectation-maximization (EM) algorithm in blind inter-symbol interference (ISI) channel estimation. This problem primarily arises from phase and shift ambiguities due to poor initialization, which blind EM estimation is inherently unable to resolve. We propose an effective initialization refinement algorithm that utilizes the decoder output as a metric for model selection. Finite candidate models are generated based on the physical properties of the channel and modulation format, incorporating a joint detection of phase and shift ambiguities. Our results show that the proposed algorithm significantly reduces the number of local maximum cases to nearly one-third for a 3-tap ISI channel under highly uncertain initial conditions. The improvement becomes more pronounced as initial errors increase and the channel memory grows. When used in a turbo equalizer, the proposed algorithm is required only in the first turbo iteration, thereby limiting any increase in complexity in subsequent iterations.

Keywords:

Blind channel estimation

expectation maximization

initialization

phase ambiguity

shift ambiguity

turbo equalization

Physics-Aware Initialization Refinement in Code-Aided EM for Blind Channel Estimation

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