Variable Forgetting Factor LS Algorithm for Polynomial Channel Model | Zendy

Amit Kumar Kohli | Zendy; Amrita Rai | Zendy; Meher Krishna Patel | Zendy

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Variable Forgetting Factor LS Algorithm for Polynomial Channel Model

Author(s) -

Amit Kumar Kohli,

Amrita Rai,

Meher Krishna Patel

Publication year - 2010

Publication title -

isrn signal processing

Language(s) - English

Resource type - Journals

eISSN - 2090-505X

pISSN - 2090-5041

DOI - 10.5402/2011/915259

Subject(s) - fading , variable (mathematics) , algorithm , channel (broadcasting) , polynomial , computer science , computational complexity theory , forgetting , mathematics , telecommunications , decoding methods , mathematical analysis , linguistics , philosophy

Variable forgetting factor (VFF) least squares (LS) algorithm for polynomial channel paradigm is presented for improved tracking performance under nonstationary environment. The main focus is on updating VFF when each time-varying fading channel is considered to be a first-order Markov process. In addition to efficient tracking under frequency-selective fading channels, the incorporation of proposed numeric variable forgetting factor (NVFF) in LS algorithm reduces the computational complexity.

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