一种异步频谱检测周期优化模型及自适应模糊调整算法
doi: 10.3724/SP.J.1146.2008.00141
An Asynchronous Spectrum Sensing Period Optimization Model and Adaptive Fuzzy Adjustment Algorithm
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摘要: 该文分析授权用户频谱使用的特性,提出以信道总损失最小为目标函数的异步检测周期优化模型,针对频谱使用特性的时变性,设计了一种检测周期自适应模糊调整优化算法。算法采用模糊逻辑及可调参数自优化方法,实现检测周期的实时自适应调整。仿真结果表明在不同授权用户频谱使用特性分布及分布参数不同变化率情况下,该算法不但有效,而且在分布参数变化波动较大时具有很好的稳定性。Abstract: Based on the analysis of primary users spectrum-usage characteristics, an asynchronous sensing period optimal model on minimal costs of channels is presented, and an Adaptive Fuzzy Adjustment Algorithm (AFAA) of spectrum sensing period is proposed for time-varying spectrum-usage characteristics. The AFAA can adjust sensing period adaptively in real time using fuzzy logic with parameters optimization. Experimental results show that the AFAA is effective under many kinds of situations where spectrum-usage probability distributives as well as the change rates of these distributive parameters are different, and has better stability when the variation of distributive parameters is high.
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