Simulation annealing and fruit fly hybrid optimization wavelet generalized discrete multi-modulus blind equalization method

A multi-mode blind equalization and simulated annealing technology, applied in baseband system components, shaping networks in transmitters/receivers, etc., to achieve the effect of reducing autocorrelation, high robustness, and reducing steady-state errors

Inactive Publication Date: 2013-12-25
南京鸿晟科技有限公司
View PDF3 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to address the defects existing in the equalization of high-order quadrature amplitude modulation signals (QAM) in the existing blind equalization technology (see literature [9] Wang Bin, Ge Lindong, Huo Yajuan. Multi-mo...

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
  • Simulation annealing and fruit fly hybrid optimization wavelet generalized discrete multi-modulus blind equalization method
  • Simulation annealing and fruit fly hybrid optimization wavelet generalized discrete multi-modulus blind equalization method
  • Simulation annealing and fruit fly hybrid optimization wavelet generalized discrete multi-modulus blind equalization method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0093] Two-path underwater acoustic channel h=[0.3132,-0.1040,0.8908,0.3134] is used, the transmitted signal is 256QAM; the weight length of the equalizer is 16; the signal-to-noise ratio is 35dB; the initial center tap is used; other parameter settings are shown in Table 1 As shown, 600 Monte Cano simulation results are shown in Figure 2:

[0094] Table 1 Simulation parameter settings

[0095] p,q value p=1,q=1 p=1,q=2 p=2,q=1 p=2,q=2 p=3,q=1 Simulation step 0.000042 0.0000082 0.000004 0.00000003 0.0000004

[0096] Figure 2 shows that GSMMA can achieve high-order QAM signal equalization, and when p=2, q=2, the equalization effect of GSMMA is the best, by Figure 2a It can be seen that when p=2, q=2, the mean square error of GSMMA is the smallest, the mean square error curve is the smoothest, and the convergence trend is the most stable. Figure 2b to Figure 2f It can be seen from the comparison of the output signal diagrams of different p a...

Embodiment 2

[0097] [Example 2] 256QAM signal optimal equalization example

[0098] Channel h=[0.005,0.009,-0.024,0.854,-0.218,0.049,-0.016]; transmit signal is 256QAM; equalizer weight length is 16; signal-to-noise ratio is 35dB; p=2, q=2; population Scale 500; Drosophila initialization position vector [-0.05, 0.05]; Drosophila population iteration step value [-0.01, 0.01]; both GSMMA and WT-GSMMA are initialized with center tap; Simulated annealing initial temperature is T=30; temp Cooling coefficient α = 0.89; k = 1; other parameter settings, as shown in Table 2, 400 times of Monte Carlo simulation results, as shown in Figure 4.

[0099] Table 2 Simulation parameter settings

[0100]

[0101] Figure 3a Show, to high-order QAM signal, the inventive method SA-FOA-WT-GSMMA has stability and applicability, steady-state error is minimum, is about 7.6dB, than FOA-WT-GSMMA, WT-GSMMA and GSMMA reduce respectively 2dB, 3dB and 3.8dB; the convergence speed is the fastest, 1200 and 800 step...

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

PropertyMeasurementUnit
Snraaaaaaaaaa
Login to view more

Abstract

The invention discloses a simulation annealing and fruit fly hybrid optimization wavelet generalized discrete multi-module blind equalization method. The method comprises initializing location vectors of fruit flies in a swarm of fruit flies to serve as the decision variable of the simulation annealing method and the fruit fly hybrid optimization method, taking an input signal of an orthogonal wavelet transformer as the input of the hybrid optimization method, determining a smell concentration function of the fruit flies by a cost function of the generalized discrete multi-modulus blind equalization method, performing simulation annealing operation on the optimal location vector of the swarm of the fruit flies obtained through the fruit fly optimization method, obtaining the global optimal location vector, which does not fall into a local minimum, of the swarm of the fruit flies, and taking the location vector as the initialization weight vector of the wavelet generalized discrete multi-modulus blind equalization method. The method, while processing high-order orthogonal amplitude modulation signals, is rapid in convergence, small in steady state error, overcomes a defect of falling into the local optimum, and has strong practicality.

Description

technical field [0001] The invention relates to a blind equalization method, in particular to a simulated annealing and fruit fly mixed optimization wavelet generalized discrete multi-mode blind equalization method. Background technique [0002] Traditional Multi-modulus Algorithm (MMA) (see literature [1] Xu Xiaodong, Dai Peichu, Xu Xiaoxia. A weighted multi-modulus blind equalization algorithm suitable for high-order QAM signals [J]. Journal of Electronics and Information Technology, 2007.6,29( 6): Rain 1352~1355. Literature [2]J.Yang, GDumont.The MultimodulusBlindequalizationandItsGeneralizedAlgorithms.2002(20)5:997-1015.) The real and imaginary parts of the QAM signal are equalized separately, effectively correcting the QAM signal phase rotation, but for high-order QAM signals, the effect of MMA equalization is still not ideal. The generalized discrete multi-mode blind equalization method uses the gradient descent algorithm to update the equalizer weight vector, which i...

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): H04L25/03
Inventor 郭业才吴珊黄友锐刘晓明
Owner 南京鸿晟科技有限公司
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