基于粘性隐马尔可夫模型的协同频谱感知算法

Cooperative Spectrum Sensing Method Based on Sticky Hidden Markov Model

为解决在频谱异构场景下传统频谱感知算法较易产生大量的空间虚警的问题,`本文提出了一种基于粘性隐马尔可夫模型的协同频谱感知算法。该算法利用次级用户的感知数据在时域和空域两方面的相关性来提高感知性能。经仿真验证可知,所提算法不仅可以有效解决传统频谱感知算法存在的空间虚警问题,而且具有较高的检测性能。

In order to solve the problem that traditional spectrum sensing algorithms are prone to generate a large number of spatial false alarms in the spectrum heterogeneous scene, a cooperative spectrum sensing algorithm based on the sticky hidden Markov model(SHMM) is proposed. The proposed algorithm improves the perception performance by taking advantage of the correlation between the secondary users in the time domain and the spatial domain. The simulation verification shows that the proposed method not only effectively solves the problem of spatial false alarms in the traditional cooperative spectrum sensing method, but also retains the high detection performance of the cooperative sensing method.