光通信网络中通信信号智能感知方法研究

在光通信网络中,通信信号的感知分为单节点感知 与多节点协作感知,其中多节点的传感因能克服多径衰弱和隐藏终端的影响而被广泛研究, 但多节点的传感知在通信开销和融合方法上仍然存在许多难题有待解决。本文提出一种量化 与编码的方法来减少当地节点与融合中心之间的通信开销,在融合方法上提出一种基于节点 特征的加权融合方法来提升融合中心的判决准确性,该融合方法有效反应各个节点在认知网 络中的实际作用。此外,为了提升感知效率,利用强化学习的方法来得升熟悉环境下的感知 效率。实验结果表明:本文中的频谱感知方法与传统方法相比在同等条件下可减少通信开销 ,提升判决准确率并减少感知时间。

Research on intelligent detection method of communication signal in optical comm unication network

In optical communication networks,the perception of communication signals can be divided into single-node perception and multi-node cooperative perception.Amo ng them,multi-node cooperative sensing is widely studied because it can overcom e the effects of multipath fading and hidden terminals.However,there are still m any problems to be solved in the communication overhead and fusion method of mul ti-node cooperative sensing.In this paper,a quantitative and coding method is p roposed ot reduce the communication overhead between the local node and the Fusi on center,and a weighted fusion method based on node feature is proposed to impr ove the judgment accuracy of fusion center,the fusion method can effectively ref lect the actual role of each node in cognitive network.In addition,reinforcement learning is used to improve the sensing efficiency in familiar environment.The experimental results show that the proposed spectrum sensing method can reduced communication overhead,improve decision accuracy and reduce sensing time under t he same conditions as traditional methods.