结合盲均衡与多信号分类

Barathram Ramkumar, T. Bose
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引用次数: 0

摘要

多用户自动调制分类器(MAMC)是多天线认知无线电(CR)接收机的重要组成部分,可以帮助无线电更好地利用频谱。MAMC在一个频带内同时识别多个用户的调制方案。多输入多输出(MIMO)盲均衡器是多天线CR接收机的另一个重要组成部分,它通过减少码间干扰(ISI)和用户间干扰(IUI)来提高符号检测性能。在CR场景中,在设计盲均衡器时最好考虑自动调制分类器(AMC)的性能。在本文中,我们提出了一种MIMO盲均衡器,它提高了多用户符号检测和基于累积的MAMC的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined Blind Equalization and Classification of Multiple Signals
A multiuser automatic modulation classifier (MAMC) is an important component of a multiantenna cognitive radio (CR) receiver that helps the radio to better utilize the spectrum. MAMC identifies the modulation schemes of multiple users in a frequency band simultaneously. A multi-input-multi-output (MIMO) blind equalizer is another important component of a multiantenna CR receiver that improves symbol detection performance by reducing inter symbol interference (ISI) and inter user interference (IUI). In a CR scenario, it is preferable to also consider the performance of the automatic modulation classifier (AMC) while designing the blind equalizer. In this paper we propose a MIMO blind equalizer that improves the performance of both multiuser symbol detection and cumulant based MAMC.
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