An integrated sparsity and model-based probabilistic framework for estimating the spatial variations of communication channels

Mehrzad Malmirchegini; Yasamin Mostofi

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An integrated sparsity and model-based probabilistic framework for estimating the spatial variations of communication channels

机译：集成的稀疏性和基于模型的概率框架，用于估计通信通道的空间变化

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摘要

In this paper, we consider estimating the spatial variations of a wireless channel, based on a small number of measurements. We propose an integrated sparsity and model-based channel prediction framework. Our approach properly takes advantage of both channel compressibility in the frequency domain and channel probabilistic characterization in the spatial domain. We test our framework using outdoor and indoor channel measurements. The results confirm the superior performance of the proposed integrated approach.

机译：在本文中，我们考虑基于少量测量来估计无线信道的空间变化。我们提出了一个集成的稀疏性和基于模型的渠道预测框架。我们的方法适当地利用了频域中的信道可压缩性和空间域中的信道概率特征。我们使用室外和室内通道测量来测试我们的框架。结果证实了所提出的集成方法的优越性能。

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来源
《Physical Communication》 |2012年第2期|p.102-118|共17页
作者
Mehrzad Malmirchegini; Yasamin Mostofi;
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作者单位

Department of Electrical and Computer Engineering, University of New Mexico, United States;

Department of Electrical and Computer Engineering, University of New Mexico, United States;

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原文格式 PDF
正文语种 eng
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关键词
estimating channel spatial variations; sparsity-based estimation; probabilistic channel modeling and estimation;

机译：估计信道空间变化;基于稀疏性的估计;概率通道建模与估计;

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An integrated sparsity and model-based probabilistic framework for estimating the spatial variations of communication channels

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