Combined super-exponential iteration blind equalization algorithm based on orthogonal wavelet transform

An orthogonal wavelet, super-exponential technology, applied in electrical components, transmission systems, etc., can solve problems such as the autocorrelation of the input signal without changing the equalizer, the algorithm is unstable, and the phase rotation cannot be quickly corrected.

Inactive Publication Date: 2009-07-08
NANJING UNIV OF INFORMATION SCI & TECH
View PDF0 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the algorithm can only work when the phase rotation is constant, and the phase rotation cannot be corrected quickly in the non-stationary underwater acoustic channel, and the hard switching method used by it will cause the algorithm to be unstable.
Literature (see: De CASTRO F C C, De CASTRO M C F. Concurrent blind deconvolution for channel equali-zation [C] Proc ICC'2001, 2: 366-371) proposed a soft handover CMA+DD algorithm, the CMA It is

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Combined super-exponential iteration blind equalization algorithm based on orthogonal wavelet transform
  • Combined super-exponential iteration blind equalization algorithm based on orthogonal wavelet transform
  • Combined super-exponential iteration blind equalization algorithm based on orthogonal wavelet transform

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] Such as figure 1 shown. The Super Exponential (SE) algorithm derives the Super Exponential Iterative (SEI) blind equalization algorithm. The SE blind equalization algorithm operates on data segments, while the SEI algorithm operates on data points, so the SEI algorithm can more effectively track the time-varying characteristics of the underwater acoustic channel. In the figure, k represents the time series, a(k) represents the signal transmitted by the transmitter, which is a white independent and identically distributed sequence with a variance of 1; c(k) is the channel impulse response vector; n(k) is the channel noise, generally assumed to be Gaussian white noise sequence and independent of signal statistics. y(k) is the input sequence of the equalizer, and y(k)=[y(k), y(k-1),..., y(k-L+1)] T ; f(k) is equalizer weight vector, and f(k)=[f(k), f(k-1),..., f(k-L+1)] T (L is the weight length, which is a positive integer, and T represents transposition); ψ(·) is a n...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a super-exponential interative combined blind equalization method based on orthogonal wavelet transformation (WT-CSEI). The WT-CSEI algorithm is implemented by incorporating the orthogonal wavelet transformation in the super-exponential interative (SEI) algorithm, correcting by use of the weight vector iterative formula of the orthogonal wavelet transformation relative to the SEI algorithm, simultaneously combining the decision directed (DD) algorithm with the soft-switching method, and introducing a phase-locked loop (PLL) technique with regard to the characteristics of time-variable Doppler frequency shift of under acoustic channel. The WT-CSEI algorithm corrects the phase rotation by means of the PLL technique, accelerates the convergence rate by means of the orthogonal wavelet transformation, reduces the steady-state error by means of the combination of the soft switching method and the DD algorithm, can effectively track the time varying characteristics of the channel, and is applied to the blind equalization of the time-variable multipath fading underwater acoustic channel.

Description

technical field [0001] The invention relates to a super-exponential iterative joint blind equalization method, in particular to a super-exponential iterative joint blind equalization method based on orthogonal wavelet transform. Background technique [0002] In underwater communication systems, limited bandwidth and multipath propagation will lead to serious inter-symbol interference (Inter-Symbol Interference, ISI), which needs to be eliminated by equalization technology at the receiving end. Compared with traditional adaptive equalization, blind equalization does not need to transmit training sequences periodically, and has high channel utilization, so it is suitable for underwater acoustic channel equalization. Among various blind equalization algorithms, Shalvi and Weinstein directly use high-order statistics to propose a super-exponential iterative blind equalization (Super-ExponentialIterative, SEI) algorithm with almost super-exponential convergence (see literature: O...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): H04B13/02
Inventor 郭业才杨超
Owner NANJING UNIV OF INFORMATION SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap