EM-based recursive estimation of channel parameters

• Published in: IEEE transactions on communications Vol. 47; no. 9; pp. 1297 - 1302
• Main Authors: Zamiri-Jafarian, H., Subbarayan Pasupathy
• Format: Journal Article
• Language: English
• Published: IEEE 01.09.1999
• Subjects: Algorithms; Approximation algorithms; Channels; Filtering algorithms; Impulse response; Least squares approximation; Linear systems; Mathematical analysis; Mathematical models; Recursive; Recursive estimation; Resonance light scattering; Stochastic processes; Stochastic resonance; Stochastic systems; Stochasticity; Vectors; Vectors (mathematics)
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/26.789663

Recursive (online) expectation-maximization (EM) algorithm along with stochastic approximation is employed in this paper to estimate unknown time-invariant/variant parameters. The impulse response of a linear system (channel) is modeled as an unknown deterministic vector/process and as a Gaussian vector/process with unknown stochastic characteristics. Using these models which are embedded in white or colored Gaussian noise, different types of recursive least squares (RLS), Kalman filtering and smoothing and combined RLS and Kalman-type algorithms are derived directly from the recursive EM algorithm. The estimation of unknown parameters also generates new recursive algorithms for situations, such as additive colored noise modeled by an autoregressive process. The recursive EM algorithm is shown as a powerful tool which unifies the derivations of many adaptive estimation methods.