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中文摘要：
在实际的认知无线电网络中不可避免地存在虚警和漏检等非理想频谱检测的情况。非理想的频谱检测会使频谱切换不准确,引起更多的不确定问题。论文在隐马尔可夫模型基础上,考虑非理想感知下,利用虚警、漏检概率对感知信息进行修正,提高对未来状态概率预测的准确性;进而对信道剩余空闲时间的计算提出了一种改进算法,并且给出了相应的切换策略。仿真结果表明,在不同虚警概率下,所提切换算法性能更优。
英文摘要：
In the actual cognitive radio network,there exist the inevitable non-ideal spectrum detection such as false alarm and missed detection which may lead to the inaccurate spectrum handoff and cause more uncertain problems.Based on the hidden Markov model,this paper considers the non-ideal spectrum detection and utilizes the false alarm and missed probabilities to modify the sensory information and to improve the prediction accuracy.Furthermore,an improved algorithm as well as the corresponding handoff strategy are proposed to calculate the channel remaining idle time.The simulation results show that the proposed algorithm has a better performance under different false alarm probabilities.
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