无线蜂窝网络中多rat优化的鲁棒干扰识别

2012 IEEE International Symposium on Dynamic Spectrum Access Networks Pub Date : 2012-10-01 DOI:10.1109/DYSPAN.2012.6478147

Emmanuel Pollakis, R. Cavalcante, S. Stańczak, F. Penna

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引用次数: 2

摘要

本研究的目的是为UMTS和LTE网络设计新的认知干扰识别技术。我们应用机器学习技术，利用先验系统知识、有限的用户信息、稀疏的路径损失和干扰测量来重建干扰模式。利用得到的干扰图构建了以节能运行为目标的多rat优化程序。

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Robust interference identification for multi-RAT optimization in wireless cellular networks

The objective of this study is to devise novel cognitive interference identification techniques for UMTS and LTE networks. We apply machine learning techniques to reconstruct interference patterns using a priori system knowledge, limited user information and sparse pathloss and interference measurements. The obtained interference patterns are used to build a multi-RAT optimization procedure aiming at energy efficient operation.

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2012 IEEE International Symposium on Dynamic Spectrum Access Networks

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