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Orthogonal wavelet transform constant modulus blind equalization algorithm based on chaos and steepest descent joint optimization

A technique of steepest descent method and orthogonal wavelet, which is applied to the shaping network and baseband system components in the transmitter/receiver, and can solve the problems of slow convergence speed and large mean square error.

Inactive Publication Date: 2012-02-15
NANJING UNIV OF INFORMATION SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the convergence speed of CMA is slow and the mean square error is large, and the weight vector of the equalizer tends to converge to different minimum points with different initializations (see literature [2] Li Jinming, Zhao Junwei, Lu Jing. Support vector machine Simulation of initialized constant modulus blind equalization algorithm [J], Computer Simulation, 2008, 25(1): 84-87)

Method used

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  • Orthogonal wavelet transform constant modulus blind equalization algorithm based on chaos and steepest descent joint optimization
  • Orthogonal wavelet transform constant modulus blind equalization algorithm based on chaos and steepest descent joint optimization
  • Orthogonal wavelet transform constant modulus blind equalization algorithm based on chaos and steepest descent joint optimization

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Embodiment

[0110] In order to verify the effectiveness of the CWTCMA of the present invention, a simulation study of the underwater acoustic channel is carried out and compared with CMA and WT-CMA.

[0111] In the simulation experiment, the underwater acoustic channel [0.3132, -0.104, 0.8908, 0.3134] is used, the signal-to-noise ratio is 25dB, and the weight length of the equalizer is 16.

Embodiment 1

[0112] [Example 1] The transmission signal is 16QAM, and the step factor μ in CMA, WT-CMA, and CWTCMA is 0.00001, 0.0002, and 0.0001, respectively, M 1 , M 2 , M 3 The values ​​are 500, 800, 20 respectively, and N is 20; all adopt the fourth tap coefficient as 1, and the rest are all 0; c i The values ​​are all 0, d i The values ​​of ζ are all 1; the first 500 points of the equalizer input data are used to initialize the weight vector when the chaos is initialized, and the initialization switching condition ζ is 10 -5 ; The simulation result of Monte Carlo simulation times is 5000 times, such as image 3 shown.

[0113] Depend on image 3 (a) It can be seen that the mean square error of CWTCMA of the present invention after convergence is about 2dB smaller than CMA, and about 0.5dB smaller than WT-CMA; the convergence speed of CWTCMA of the present invention is about 5000 steps faster than CMA, and about 1000 steps faster than WT-CMA ;Depend on image 3 From (c) to (e),...

Embodiment 2

[0114] [Example 2] The transmission signal is 16PSK, and the step factor μ in CMA, WT-CMA, and CWTCMA is 0.001, 0.002, and 0.001, respectively, M 1 , M 2 , M 3 The values ​​are 300, 800, 20 respectively, and N is 20; all adopt the fourth tap coefficient as 1, and the rest are all 0; c i The values ​​are all 0, d i The values ​​of are all 1; the weight vector is initialized with the first 300 points of the equalizer input data during the chaos initialization, and the initialization switching condition ζ is 10 -5 ; The simulation result of Monte Carlo simulation times is 5000 times, such as Figure 4 shown. Figure 4 (a) shows that, on steady-state error, CWTCMA of the present invention reduces about 5dB than CMA, is basically the same with WT-CMA; On convergence speed, CWTCMA of the present invention is faster than CMA by nearly 4200 steps faster than WT-CMA About 1500 steps; by Figure 4 From (c) to (e), it can be seen that the equalized constellation diagram of CWTCMA i...

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Abstract

The invention discloses an orthogonal wavelet transform constant modulus blind equalization algorithm based on chaos and steepest descent joint optimization. The algorithm comprises the following steps of: causing a transmitted signal a(n) to pass through a pulse response channel c(n) to obtain a channel output vector x(n); obtaining an input signal y(n) of an orthogonal wavelet transformer (WT) by adopting channel noises w(n) and the channel output vector x(n); causing the y(n) to pass through the orthogonal WT to obtain equalizer input R(n) and equalizer output z(n); combining a chaos optimization algorithm and a steepest descent method by adopting a short segment of initial data to optimize a weight vector to make the optimized weight vector hop from a local optimal point and approach a global optimal point; and preprocessing an input signal of an equalizer by utilizing the high decorrelation of orthogonal wavelet transform to reduce the autocorrelation of the input signal and accelerate convergence. Simulation results of an underwater acoustic channel show that the orthogonal wavelet transform constant modulus blind equalization algorithm based on the chaos and steepest descent joint optimization is relatively faster in convergence, relatively higher in convergence accuracy and relatively lower in remainder error.

Description

technical field [0001] The invention relates to an orthogonal wavelet constant modular blind equalization method optimized jointly by chaos and steepest descent method. Background technique [0002] In modern underwater acoustic communication, intersymbol interference (ISI) caused by limited bandwidth and multipath propagation distorts the transmitted signal and generates bit errors at the receiving end, which affects the quality of the communication system. In order to suppress intersymbol interference, a blind equalization algorithm that does not require training sequences is usually used. Among various blind equalization algorithms, Constant Modulus Algorithm (CMA), due to its simple structure, small amount of calculation, and good stability, can adapt to general digital communication systems and is widely used in various digital transmission systems ( See literature [1] Abrar S; Nandi AK. An adaptive constant modulus blind equalization algorithm and its stochastic stabi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L25/03H04L25/02
Inventor 郭业才徐文才许芳
Owner NANJING UNIV OF INFORMATION SCI & TECH
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