Signal separation and classification algorithm for cognitive radio networks
Signal separation and classification algorithm for cognitive radio networks
复制标题
认知无线电网络的信号分离和分类算法
DOI：
10.1109/iswcs.2012.6328378
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
D. Slock
中科院分区：
文献类型：
--
作者：
Wael Guibène;D. Slock
在频谱共享的背景下，开发了许多方法，并提出了许多算法，以建模和规范频谱资源的使用。尽管提出了解决方案和频谱接入策略，但在认知无线电网络中仍然存在一个大问题，用户可能打算（或不打算）违反这些通信规则，并迫使他们的无线电在其他一些用户已经在通信时接入频带。这些用户成为网络中的敌对终端，融合中心必须消除他们的干扰信号。在这种情况下，我们提出了一种混合信号分离和分类算法，有助于消除敌对设备。第一步是定位敌对终端通信的频带，然后通过某种混合信号分离技术，通过分析从混合信号中获得的信号来隔离并消除其干扰信号。对于模拟，我们引入了一些度量的概率检测和分类的敌对终端。
In the context of spectrum sharing, many approaches were developed and many algorithms were proposed in order to model and regulate the use of spectral resources. Despite the proposed solutions and spectrum access policies, there is still a big issue in cognitive radio networks with users who may intend (or not) to violate these communication rules and force their radios to access the spectrum bands when some other users are already communicating. These users become hostile terminals in the network and the fusion center has to eliminate their interfering signals. In this context we1 propose a mixed signals separation and classification algorithm that helps eliminating hostile devices. The first step consists in locating the frequency band over which the hostile terminal is communicating and then, by some mixed signals separation technique, isolate and then eliminate its interfering signal by analyzing the obtained signals from the mixture. For the simulations, we introduced some metric for the probability of detecting and classifying the hostile terminal as such.