CLC number: TN929

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Received: 2004-03-03

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ZHANG Ji-dong, ZHENG Bao-yu, FU Hong-liang. A novel constant modulus array for multiuser detection[J]. Journal of Zhejiang University Science A, 2005, 6(1): 38-42.

@article{title="A novel constant modulus array for multiuser detection",

author="ZHANG Ji-dong, ZHENG Bao-yu, FU Hong-liang",

journal="Journal of Zhejiang University Science A",

volume="6",

number="1",

pages="38-42",

year="2005",

publisher="Zhejiang University Press & Springer",

doi="10.1631/jzus.2005.A0038"

}

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%A ZHANG Ji-dong

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%I Zhejiang University Press & Springer

%DOI 10.1631/jzus.2005.A0038

TY - JOUR

T1 - A novel constant modulus array for multiuser detection

A1 - ZHANG Ji-dong

A1 - ZHENG Bao-yu

A1 - FU Hong-liang

J0 - Journal of Zhejiang University Science A

VL - 6

IS - 1

SP - 38

EP - 42

%@ 1673-565X

Y1 - 2005

PB - Zhejiang University Press & Springer

ER -

DOI - 10.1631/jzus.2005.A0038

**Abstract: **This paper proposes a new multitarget constant modulus array structure for code division multiple access (CDMA) systems. The new algorithm for the structure is called pre-despreading and wavelet denoising constant modulus algorithm (D-WD-CMA). In the new algorithm, the pre-despreading is applied to multitarget arrays to remove some multiple access interferences. After that the received signal is subjected to wavelet de-noising to reduce some noise, and used in CMA adaptive iteration for signal separation. Simulation results showed that the proposed algorithm performed better than the traditional CMA algorithm.

**
**

. INTRODUCTION

ing is an effective method to alleviate the capture problem and make the CMA adaptive array be available in CDMA systems (Zhu et al.,

Based on the idea above, a new multitarget constant modulus array for multiuser detection in CDMA systems is presented in this paper. The proposed algorithm is called pre-despreading and wavelet denoising CMA algorithm (D-WD-CMA). Simulation results showed that the D-WD-CMA algorithm can improve the system performance.

. SIGNAL MODEL

. DENOISING BASED ON WAELET TRANSFORM

For signal reconstruction, two sequences {

For more details, the reader is referred to (Chui,

Let

. D-WD-CMA ALGORITHM

the updating of weight vector at time instant

Assume the desired user is

Then Eq.(

After wavelet denoising, Eq.(

Substituting Eq.(

The pre-despreading involves

According to the theory of wavelet de-noising, the complexity of wavelet de-noising mainly depends on the wavelet decomposition and reconstruction because the selection of threshold and thresholding the detail coefficients require little calculation, compared with the wavelet decomposition and reconstruction. The D-WD-CMA algorithm’s wavelet decomposition needs at most 4(

The complexity of the CMA algorithm is somewhat reduced because the iteration is based on the symbol, not chip signal. According to Eqs.(

To sum up, the higher cost of the D-WD-CMA algorithm is due to its increased complexity, compared with the LSCMA algorithm. When applying the D-WD-CMA algorithm, we can select some wavelets of requiring few calculations, decrease the decomposition levels and the array elements to reduce the complexity, and lead to numerical difficulties.

. SIMULATIONS

Fig.

best choice because it can reduce the noise better, while the wavelet denoising (

BER performance vs different thresholds is illustrated in Fig.

. CONCLUSION

* Project supported by the National Natural Science Foundation of China (No. 60372107) and the Hi-Tech Research and Development Program (863) of China (No. 2002AA121068)

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