认知无线电网络中基于预测的频谱感知方案

Prediction based spectrum sensing scheme in cognitive radio networks

为降低认知无线电网络的能耗,提高频谱感知的精度,提出一种基于预测的协作频谱感知方法。通过隐马尔可夫预测算法,剔除不可靠节点,降低频谱感知的不可靠性;基于剩余能量和全局检测概率选择协作频谱感知节点,对频谱状态决策进行优化,实现延长网络生命时间,提高协作频谱感知精度的目标。仿真结果表明,在不降低频谱感知准确率的前提下,该方法有效降低了能耗。

To decrease the energy consumption in cognitive radio networks(CRNs)and improve the accuracy of spectrum sen-sing,a prediction based cooperative spectrum sensing method was proposed.Through hidden Markov model based prediction algorithm,the unreliable nodes were eliminated and the spectrum sensing accuracy was improved.The nodes performing cooperative spectrum sensing were selected based on the remaining energy and global detection probability to optimize the performance of spectrum status decision.The network lifetime was then prolonged and the accuracy of cooperative spectrum sensing was improved.The simulation results show that the proposed method can reduce the energy consumption efficiently while the spectrum sensing accuracy is guaranteed.