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Nakagami-m信道下认知中继网络的中断概率上界闭式解模型

A Closed-Form of Upper Bound for Outage Probability in Cognitive Relay Networks Based on Nakagami-m Fading Channels

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【作者】 刘阳冯志勇尉志清张平

【Author】 LIU Yang,FENG Zhiyong,WEI Zhiqing,ZHANG Ping(Key Laboratory of Universal Wireless Communication,Ministry of Education,Beijing University of Posts and Communication,Beijing 100876,China)

【机构】 北京邮电大学泛网无线通信教育部重点实验室

【摘要】 为更准确地反映和评估无线信道衰落指数对认知中继网络中断性能的影响,提出了认知用户在Nakagami-m信道模型下的中断概率上界闭式解模型.首先在Nakagami-m信道模型下,对认知中继网络频谱重叠共享和最佳中继选择准则的联合约束限制进行分析,再利用分部积分推导出认知用户接收机信噪比的概率密度函数和累积分布函数,进而对概率密度函数进行条件积分,根据蕴含法则即事件概率不等式得出其中断概率上界闭式解模型.仿真结果表明:相比传统的瑞利信道模型,Nakagami-m信道模型下的中断概率闭式解能够反映信道衰落指数大于1时的系统中断性能,从而更准确地反映了实际信道衰落情况对认知中继网络的影响;此外,由于该闭式解模型考虑了主用户干扰限制条件,限制了认知用户的实际发射功率,因而降低了系统的中断概率.

【Abstract】 A closed-form of the upper bound for the outage probability is derived in Nakagami-m channel model to effectively estimate the impact on outage probability of cognitive relay networks from the wireless channel fading exponent.Firstly,joint constraints of the spectrum underlay sharing and the best relay selection criteria are analyzed.Then,the probability density function and cumulative distribution function of the signal to noise ratio at the secondary receiver node are obtained using the subsection integral.The conditional integral of the probability density function is performed,and the closed-form of the upper bound for the outage probability is derived according to the implication rules.Simulation results and comparisons with the traditional Rayleigh channel model show that the outage probability performance with fading exponent greater than one can be effectively estimated by the Nakagami-m channel model.Furthermore,the outage probability is reduced because the power of cognitive users is limited under the constraint of the interference temperature of primary users.

【基金】 国家自然科学基金创新研究群体科学基金资助项目(61121001);国家“973计划”资助项目(2009CB320400);国家科技重大专项基金资助项目(2010ZX03003-001-01);科技部中芬合作资助项目(2010DFB10410)
  • 【文献出处】 西安交通大学学报 ,Journal of Xi’an Jiaotong University , 编辑部邮箱 ,2012年10期
  • 【分类号】TN925
  • 【被引频次】2
  • 【下载频次】156
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