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Variable forgetting factor linear least squares algorithm for frequency selective fading channel estimation
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DOI：10.1109/TVT.2002.1002509.png)
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摘要
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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.
Keyword:
fading channel estimation
linear least squares (LLS)
variable forgetting factor (VFF)
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期刊
IF:
7.1
论文数:
1.8W
被引数:
6.6W
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STATIONARY AND NONSTATIONARY LEARNING CHARACTERISTICS OF LMS ADAPTIVE FILTER.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
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