Optimal forgetting factor-based semi-blind recursive least squared (RLS) channel estimation method

A forgetting factor and channel estimation technology, applied in the field of semi-blind recursive least squares channel estimation technology, can solve problems such as reducing system operation efficiency and increasing computing time.

Inactive Publication Date: 2011-08-17
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

Therefore, this inefficient method of obtaining the optimal forgetting factor seriously increases the calculation time and reduces the operating efficiency of the system.

Method used

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  • Optimal forgetting factor-based semi-blind recursive least squared (RLS) channel estimation method
  • Optimal forgetting factor-based semi-blind recursive least squared (RLS) channel estimation method
  • Optimal forgetting factor-based semi-blind recursive least squared (RLS) channel estimation method

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Embodiment Construction

[0044] In this embodiment, the Matlab2007b simulation platform is used for running experiments. OFDM system parameters: subcarrier 512, cyclic prefix 88, symbol bandwidth 10M, symbol period T s =60us, the number of pilot symbols is 4, and the number of data symbols is 20. The wireless channel environment is the Doppler frequency shift f d =200Hz COST207TU fading channel model, the channel autocorrelation function is the first kind of zero-order Bessel function J 0 (g), ie r(i,j)=J 0 (2πf d T s (i-j)).

[0045] Implementation steps such as figure 1 Shown:

[0046] I. Obtaining the optimal forgetting factor: Obtaining the optimal forgetting factor through a step-by-step traversal search algorithm. If the current SNR is 0dB:

[0047] First, within the interval [0.05, 0.95], iteratively calculates the MSE corresponding to different forgetting factor values ​​with a step size of 0.1, such as MSE (i=50) when the 50th OFDM symbol is received. According to the MSE formula, w...

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Abstract

The invention provides a semi-blind recursive least squared (RLS) channel estimation method, which is applied to a single input single output orthogonal frequency division multiplexing (OFDM) system. In the semi-blind RLS channel estimation method, an optimal forgetting factor can be rapidly acquired. In the method, mean square error performance in semi-blind RLS channel estimation is analyzed to obtain an accurate mean square error calculation formula, and an optimal forgetting factor value can be obtained by utilizing the mean square error calculation formula and a stepwise traversing searching algorithm, so the optimal forgetting factor can be rapidly obtained without a time-consuming emulation process. In the method, the optimal forgetting factor value can be flexibly changed according to signal to noise ratio condition and an autocorrelation function of a fading channel; therefore, the method is more widely applied, relatively lower in calculation complexity and relatively higher in realization efficiency, the optimal forgetting factor calculation efficiency is remarkably improved, and the problem of low semi-blind RLS channel estimation efficiency of the conventional single input single output OFDM system is solved.

Description

technical field [0001] The invention belongs to Orthogonal Frequency Division Multiplexing (OFDM) channel estimation technology in wireless communication technology, in particular to a semi-blind Recursive Least Squared (Recursive Least Squared, RLS) channel estimation technology. Background technique [0002] Orthogonal frequency division multiplexing system is a wireless communication system with high data rate multi-carrier transmission. It has been widely used in signal transmission of wireless communication networks. However, due to the Doppler effect generated by terminal movement and the shadow effect caused by obstacles, wireless channels exhibit dramatically changing fading characteristics and multipath delay characteristics. Therefore, for OFDM receivers using coherent detection, channel estimation of wireless fading channels is a crucial issue. [0003] The channel estimation technology based on Recursive Least Squared (RLS) adaptive filtering algorithm has stro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L25/02
Inventor 黄彪王军唐万斌李少谦
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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