Blind spectrum sensing for cognitive radio over time-variant multipath flat-fading channels
Blind spectrum sensing for cognitive radio over time-variant multipath flat-fading channels
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DOI：
10.1186/1687-1499-2014-84
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发表时间：
2014-05
影响因子：
2.6
通讯作者：
Cheng-lin Zhao;Mengwei Sun;Bin Li;Long Zhao;Xiao Peng
中科院分区：
文献类型：
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作者：
Cheng-lin Zhao;Mengwei Sun;Bin Li;Long Zhao;Xiao Peng
认知无线电近年来得到了越来越广泛的应用，它可以在时变多径平衰落信道通信系统等复杂的无线环境条件下工作。作为认知无线电的一项重要技术，现有的频谱感知方法大多是针对时不变传播信道设计的；因此，当我们将它们应用于时变多径衰落信道时，很难获得可接受的传感性能。为了克服这一障碍，本研究设计了一种新的频谱感知方法。首先，提出了一种动态状态空间模型，该模型采用两种不同的隐马尔可夫模型来抽象主用户状态的演化和时变多径平坦衰落信道增益。基于动态状态空间模型，将频谱感知问题表述为盲估计问题。基于最大后概率准则和粒子滤波技术，提出了时变信道增益和用户主状态的联合估计算法。实验仿真结果表明，本文提出的传感方案具有良好的性能，可用于现实的认知无线电系统。
Cognitive radio has more extensive application in recent years, and it may operate in complex wireless environmental condition such as communication systems with time-variant multipath flat-fading channel. As an essential technology for cognitive radio, most existing spectrum sensing methods are designed for time-invariant propagation channel; thus, it could be extremely difficult to achieve acceptable sensing performance when we apply them to deal with time-variant multipath fading channel. In order to overcome this obstacle, we design a novel spectrum sensing method in this investigation. Firstly, a dynamic state-space model is proposed in which two different hidden Markov models are employed to abstract the evolution of primary user state and time-variant multipath flat-fading channel gain. Based on the dynamic state-space model, the spectrum sensing problem is formulated as blind estimation problem. Relying on maximuma posterioriprobability criterion and particle filtering technology, a joint estimation algorithm of the time-variant channel gain and primary user state is presented. Experimental simulations demonstrate the superior performance of our presented sensing scheme, which could be used potentially in realistic cognitive radio systems.