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引用次数: 7

摘要

提出了一种用于短突发异步DS-CDMA系统的半盲时空均衡和多用户检测策略。该技术首先进行半盲子空间信道识别,然后通过恒模算法(CMA)进行半盲均衡。通过加入通信信号的常模特性和环平稳特性,对传统的基于训练的最小二乘估计进行了改进。仿真结果表明,与正则化LS估计器(基于训练和半盲)相比,所需的训练符号数量(对于短数据突发)显著减少。应用于第三代DS-CDMA系统的反向链路。
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Semi-blind spatio-temporal equalization and multiuser detection for DS-CDMA systems
We propose a novel strategy for semi-blind spatio-temporal equalization and multiuser detection for short-burst asynchronous DS-CDMA systems. The technique is based on first performing semi-blind subspace-based channel identification and then semi-blind equalization via the constant modulus algorithm (CMA). In this way we are able to improve upon the traditional training-based least squares (LS) estimator by adding the constant modulus and cyclostationary properties of communication signals. Simulation results indicate a significant reduction in the required number of training symbols (for a short burst of data) compared with regularized LS estimators (both training-based and semi-blind). Application is in the reverse link of third-generation DS-CDMA systems.
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