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华东某水库表层沉积物氨氮释放贡献量分析
引用本文:任梦梦,胡燕妃,翟旭平.华东某水库表层沉积物氨氮释放贡献量分析[J].上海大学学报(自然科学版),2021,27(1):49-56.
作者姓名:任梦梦  胡燕妃  翟旭平
作者单位:1.上海城投原水有限公司, 上海 200125;2.上海大学 环境与化学工程学院, 上海 200444;3.同济大学 环境科学与工程学院, 上海 200092
基金项目:国家自然科学基金资助项目(61171085);国家自然科学基金资助项目(61401266)
摘    要:通过对华东某水库进行现场水样采样, 并结合沉积物氨氮释放试验, 分析水库典型区域表层沉积物、上覆水和间隙水中总氮、氨氮含量, 揭示氮素组成的时空分布特征和表层沉积物对上覆水氨氮的影响. 结果表明: 库内氨氮和总氮呈现明显的季节变化, 且冬季明显高于夏季; 表层沉积物中总氮的质量浓度高于上覆水, 沉积物氨氮扩散通量为 0.18$\sim认知无线电中频谱感知方法的性能与感知场景高度相关. 研究表明, Nakagami-Gamma(KG)衰落信道模型能够可靠地描述无线通信信道. 针对采样点数、接收信噪比、地理位置等多种性能影响因素各不相同的一组异构节点在KG衰落信道下的感知场景, 提出了一种基于熵函数(based on entropy function, BEF)的合作感知方法. 首先, 根据异构节点的不同性能影响因素, 通过定义的熵函数计算各节点的综合评价得分; 然后, 筛选出得分较高的节点进行标准化能量检测; 最后, 采用逻辑或(OR)准则进行融合判决. 仿真结果表明, BEF方法有效地降低了系统的感知开销, 在各个节点的目标虚警概率较低($P_{\rm f}<0.1$)时, 显著提升了全局检测概率.

关 键 词:沉积物  上覆水  间隙水  氮转化  吸附  解吸  
收稿时间:2018-11-14

Cooperative spectrum sensing method based on entropy function
REN Mengmeng,HU Yanfei,ZHAI Xuping.Cooperative spectrum sensing method based on entropy function[J].Journal of Shanghai University(Natural Science),2021,27(1):49-56.
Authors:REN Mengmeng  HU Yanfei  ZHAI Xuping
Institution:1. Shanghai Chengtou Raw Water Co., Ltd., Shanghai 200125, China;2. School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China;3. College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
Abstract:In cognitive radio, the performance of the spectrum sensing method is closely related to the sensing scene. Research has shown that the Nakagami-Gamma (KG) fading channel model can reliably describe wireless communication channels. A cooperative sensing method based on the entropy function (BEF) is proposed for the sensing scene of heterogeneous nodes (a group of nodes with different performance factors such as sampling number, receiving signal-to-noise ratio (SNR), and geographical location) in the KG fading channel. First, the comprehensive evaluation scores of each node are calculated using the defined entropy function according to the different performance factors of heterogeneous nodes. Then, the nodes with high scores are selected for normalised energy detection. Finally, the OR criterion is used for fusion decision. Simulation results show that the proposed BEF method can effectively reduce the overhead of the sensing system, and the global detection probability is significantly improved when the target false alarm probability of each node is low ($P_{\rm f}<0.1$).
Keywords:spectrum sensing  Nakagami-Gamma (KG) fading channel  heterogeneous nodes  entropy function  
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