一种基于马尔科夫链的水下频谱预测方法

随着现代信息技术和海洋开发技术的飞速发展，人们对水声通信的需求日益增加。本文针对水声信道可用通信带宽有限、传输时延大的特性，提出了一种基于马尔科夫链的认知水声通信中的频谱预测方法，并用MATLAB对其性能进行了仿真。仿真结果显示与无频谱预测及随机接入情况下相比，本文所提方法可以合理地动态分配水下的频谱资源、有效的减少数据碰撞概率，从而提高频道利用率以及节点接入频道的准确率。

A Spectrum Prediction Method Based on Markov Chain Underwater

With the rapid development of the modern information technology and ocean exploitation, the demand for underwater acoustic communication is increasing. However, due to the special underwater environment, it is extremely shortage of the available bandwidth and large transmission delay in the underwater acoustic communication. Therefore, this paper proposes a spectrum prediction method based on Markov chain in cognitive underwater acous- tic communication,then uses MATLAB to simulate this method and analyzes its performance. The simulation results show that, compared with the situation under no spectrum prediction, this method can effectively reduce the data collision probability and improve the channel utilization and the channel- access accuracy of the nodes.