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自回归信道模型研究 被引量：2

Research of autoregressive channel models
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摘要 高效、可靠地检测频谱空洞是认知无线电研究的重要技术。采用基于卡尔曼滤波的自回归信道预测模型可较好地估计频谱空洞,自回归模型常用于近似离散时间随机过程。首先讨论了ALOHA系统中认知用户和授权用户共存的系统模型;其次采用p阶模型近似平坦瑞利衰落信道,对瑞利衰落信道进行了仿真,给出了求解模型参数的算法,并讨论了p阶模型的平稳性。仿真实验表明,自回归信道模型的自相关函数能较好地和理论值匹配,而且易于实现。 Efficient and reliable detection of spectrum holes is an important technology for cognitive radio.Autoregressive channel models based on Kalman filtering can estimate the spectrum holes well,and are commonly used to approximate discrete-time random processes.Firstly,this paper discusses the system model of the coexistence with rental users and licensed users for ALOHA system.Secondly,an AR model of order p is used to approximate the flat Rayleigh fading channels.The simulation is performed.An algorithm for solving the AR model parameters is given,and its stability is also discussed.Simulation results show that the autocorrelation of autoregressive channel models can better match the theoretical value,and implement easily.
作者 董春利 董育宁 王莉
机构地区 南京邮电大学通信与信息工程学院 南京交通职业技术学院信息工程系 苏州大学江苏省计算机信息处理技术重点实验室
出处 《计算机工程与应用》 CSCD 北大核心 2009年第20期103-105,共3页 Computer Engineering and Applications
基金 教育部科学技术研究重点项目No.205060 江苏省高校自然科学重大基础研究项目No.07KJA51006 江苏省计算机信息处理技术重点实验室苏州大学开放基金No.KJS0712 华为公司科技基金~~
关键词 认知无线电 频谱空洞 瑞利衰落信道 模型 cognitive radio spectrum hole Rayleigh fading channel AR model
分类号 TN911.23 [电子电信—通信与信息系统]
  • 相关文献

参考文献11

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二级参考文献4

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共引文献2

同被引文献23

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计算机工程与应用
2009年 第20期

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