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A Kind of Online Support Vector Machine for Blind Multi-user Detection

机译:一种用于盲多用户检测的在线支持向量机

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CDMA is a time-varying system. The background noise of channel and the relative position between base stations and users are continuous, the joining and leaving of users are stochastic, These factors result in that the properties of signal received by users are changing continuously. Based on this, we propose a online support vector machine for blind multi-user detection method. The main idea of this method is that the detector updates the training dataset periodically and retrains the SVM classifter with an incremental training algorithm. So we can trace the changing of the system and improve the performance of the signal detection.
机译:CDMA是随时间变化的系统。信道的背景噪声和基站与用户之间的相对位置是连续的,用户的加入和离开是随机的,这些因素导致用户接收到的信号的特性不断变化。基于此,我们提出了一种用于盲多用户检测的在线支持向量机。该方法的主要思想是检测器会定期更新训练数据集,并使用增量训练算法对SVM分类器进行再训练。因此,我们可以跟踪系统的变化并提高信号检测的性能。

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