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Method of ideal decision weighted time-varying step-size RLS

A time-varying step size and decision technology, applied in the field of channel estimation, can solve problems such as poor performance and suboptimal algorithms

Inactive Publication Date: 2007-07-18
UNIV OF ELECTRONICS SCI & TECH OF CHINA ZHONGSHAN INST
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In the literature T.R.Fortescue, L.S.Kershenbaum, and B.E.Ydstic. "Implementation of self-tuning regulators with variable forgetting factors", Automatica, vol1.17, No.6, pp.831-835, 1981. Using time-varying forgetting factors to track features changes, poor performance
In the literature E.Eleftherion and D.D.Falconer, "Tracking properties and performance of RLS adaptive filter algorithms", IEEE Trans.Acoust.Acoust, Signal Processing, vol1.34, No.5, pp.1097-1109, Oct.1986. and literature S.D.Peters and A.Antonion, "A parallel adaptation algorithm for recursive-least-squares adaptive filters in nonstationary environments", IEEE Trans.Signal Processing. vol1.43, No.11, pp.2484-2495, Nov.1995. Adopted Time-varying forgetting factors to improve tracking of time-varying features, but in dynamic systems, these algorithms are not optimal

Method used

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  • Method of ideal decision weighted time-varying step-size RLS
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  • Method of ideal decision weighted time-varying step-size RLS

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Embodiment Construction

[0028] The technical solution of the present invention will be further described through specific implementation below.

[0029] The specific steps are:

[0030] 1. The sending end sends in the OFDM modulated baseband signal to generate a guard interval, and generates a transmit signal through the D / A and shaping filter.

[0031] 2. At the receiving end, after the received signal passes through the A / D and low-pass filter, the guard interval is deleted, and the received signal matrix Y is obtained.

[0032] Y=Xh+v (1)

[0033] 3. Set parameter μ 0 , the value of a, b, calculate the step size matrix μ n . in:

[0034] mu n = α n ×μ 0 (2)

[0035] α n = C 1 1 + an b - - - ( 3 )

...

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Abstract

This invention provides an ideal judged weighting time varying RLS method to improve convergency speed of algorithm and get the best filter weighting coefficient and applies ideal judgement weighting to maintain the Rodust of hard judgement errors and channels noises, which is an adaptive blind estimation method with quicker convergency speed and higher estimation accuracy than the current recursion least square technology not only used in OFDM, CDMA and TDMA communication systems bur also character parameter estimations relating to different fields.

Description

Technical field: [0001] The invention relates to an ideal decision weighted time-varying step size RLS method, which belongs to various fields such as communication, petroleum seismic exploration, radar, remote control telemetry, aerospace, image processing, etc., and especially relates to channel estimation in OFDM, CDMA and TDMA communication systems technology. Background technique: [0002] Adaptive signal processing is an important branch of signal and information processing in information science, and it is the main content of statistical signal processing and non-stationary signal processing. This technology has extremely important applications in communication, seismic exploration, sonar, image processing, computer vision, biomedical engineering, vibration engineering, radar, remote control telemetry, aerospace and other fields. [0003] As an important method in adaptive algorithm, RLS algorithm is often used in system identification, inverse identification, predic...

Claims

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Application Information

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IPC IPC(8): H04L25/02
Inventor 罗仁泽
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA ZHONGSHAN INST