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Variable forgetting factor linear least squares algorithm for frequency selective fading channel estimation
DOI:10.1109/TVT.2002.1002509.png)
Abstract
En 中文
In this correspondence, the variable forgetting factor linear least squares algorithm is presented to improve the tracking capability of channel estimation. A linear channel model with respect to time change describes a time-varying channel more accurately than a conventional stationary channel model. To reduce estimation error due to model mismatch, we incorporate the modified variable forgetting factor into the proposed algorithm. Compared to the existing algorithms-exponentially windowed recursive least squares algorithm with the optimal forgetting factor and linear least squares algorithm-the proposed method makes a remarkable improvement in a fast fading environment. The effects of channel parameters such as signal-to-noise ratio and fading rate are investigated by computer simulations.
Keywords:
fading channel estimation
linear least squares (LLS)
variable forgetting factor (VFF)
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Journal
IF:
7.1
Papers:
1.8W
Citations:
6.6W
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No organization information available
Cited Papers
STATIONARY AND NONSTATIONARY LEARNING CHARACTERISTICS OF LMS ADAPTIVE FILTER
PROCEEDINGS OF THE IEEE
IF25.9
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