一種基于波形集設計的降低異步DS-CDMA系統(tǒng)多址干擾的新方法

郭黎利; 李清偉; 董雪

doi:10.11999/JEIT161055

一種基于波形集設計的降低異步DS-CDMA系統(tǒng)多址干擾的新方法

doi: 10.11999/JEIT161055

基金項目:

國家自然科學基金(61271263)

計量
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出版歷程
- 收稿日期: 2016-10-12
- 修回日期: 2017-01-11
- 刊出日期: 2017-07-19

A Novel Method to Reduce the Multi-address Interference for Asynchronous DS-CDMA System Based on Waveform-sets Designing

Funds:

The National Natural Science Foundation of China (61271263)

摘要

摘要: 已有研究指出，在異步DS-CDMA系統(tǒng)中，每個用戶chip碼元使用常規(guī)7種波形中的雙波形(DW)可以有效地降低多址干擾。該文提出一種基于波形集(WS)設計降低多址干擾的新方法。對于任意多的用戶，均可以設計出由常規(guī)7種波形中2種或者3種波形構成的WS。相對于DW方法，每個用戶只需要使用WS中的單一波形就可以進一步提升其輸出端的信干噪比(SINR)和誤碼率(BER)性能。該文不僅給出了新方法中使用不同波形用戶接收端的SINR計算公式，同時給出了不同波形用戶改進高斯近似 (IGA)下的BER。理論推導和實驗仿真證實了：IGA與高斯近似 (GA)的BER相比，具有與實際仿真曲線更好的重合度；新方法IGA下BER推導的準確性；基于WS的新方法相對于已有的DW方法可以進一步降低MAI以及提升多用戶的SINR和BER性能。
- 異步DS-CDMA; 波形集 /
- 信干噪比 /
- 改進高斯近似 /
- 誤碼率
Abstract: It is shown that the Multi-Address Interference (MAI) can be effectively reduced when Double Waveforms (DW) are used with chip code in the asynchronous DS-CDMA system. A novel method to reduce the MAI based on Waveform Sets (WS) is proposed. For any number of users, each user can choose single waveform from the WS that can be designed with only two or three kinds of seven conventional waveforms, and can obtain better Signal to Interference plus Noise Ratio (SINR) and Bit Error Rate (BER) performance than DW method. The analytical expression of SINR at the output of each correlation receiver for the proposed method is given. Besides, the BER by Improved Gaussian Approximation (IGA) over an additive white Gaussian noise channel is derived. Relative to the existing DW method, it is shown that the proposed method can further improve the SINR and BER performance through theoretical analysis and simulation results. The overlap between simulation curves and theoretical BER curves with IGA proves that the accuracy of BER with IGA outweighs BER with Gaussian approximation (GA).
- Asynchronous DS-CDMA /
- Waveform Sets (WS) /
- Signal-to-Interference-plus-Noise Ratio (SINR) /
- Improved Gaussian Approximation (IGA)

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