The error patterns of a wireless channel can be represented by a binary sequence of ones(burst) and zeros(run),which is referred to as a trace.Recent surveys have shown that the run length distribution of a wireless c...The error patterns of a wireless channel can be represented by a binary sequence of ones(burst) and zeros(run),which is referred to as a trace.Recent surveys have shown that the run length distribution of a wireless channel is an intrinsically heavy-tailed distribution.Analytical models to characterize such features have to deal with the trade-off between complexity and accuracy.In this paper,we use an independent but not identically distributed(inid) stochastic process to characterize such channel behavior and show how to parameterize the inid bit error model on the basis of a trace.The proposed model has merely two parameters both having intuitive meanings and can be easily figured out from a trace.Compared with chaotic maps,the inid bit error model is simple for practical use but can still be deprived from heavy-tailed distribution in theory.Simulation results demonstrate that the inid model can match the trace,but with fewer parameters.We then propose an improvement on the inid model to capture the 'bursty' nature of channel errors,described by burst length distribution.Our theoretical analysis is supported by an experimental evaluation.展开更多
In this paper, a multi-hop relay channel model based on unmanned aerial vehicles(UAVs) is established by taking into account of the propagation loss, shadowing, and multi-path fading. Based on the proposed channel mod...In this paper, a multi-hop relay channel model based on unmanned aerial vehicles(UAVs) is established by taking into account of the propagation loss, shadowing, and multi-path fading. Based on the proposed channel model, the cascaded propagation loss of relay link and the cascaded probability density function(PDF) of channel fading are derived. Moreover, the theoretical performance of the UAV-based relay system, i.e., the outage probability, bit error rate(BER), and channel capacity, is also analysed and derived. Simulation results show agreement with theoretical results for the hill, mountain, and sea scenarios, indicating the accuracy of both the simulations and derivations.展开更多
针对气象变化对自由空间光(Free Space Optical,FSO)通信链路和毫米波射频(Radio Frequency,RF)通信链路可用率的影响问题,采用马尔科夫建模与稳态概率求解计算方法,分析不同天气条件下FSO/RF混合链路的双接收站分集与中断概率性能.基于...针对气象变化对自由空间光(Free Space Optical,FSO)通信链路和毫米波射频(Radio Frequency,RF)通信链路可用率的影响问题,采用马尔科夫建模与稳态概率求解计算方法,分析不同天气条件下FSO/RF混合链路的双接收站分集与中断概率性能.基于FSO链路和RF链路的信道模型,采用有限状态马尔科夫链(Finite State Markov Chain,FSMC)分别对单双站FSO/RF混合链路的切换选择进行建模,推导得出不同参数和天气情况下系统稳态的中断概率表达式.数值计算结果表明,当中断概率达到10^(-6),雨雾天气链路距离为1~7 km时,双站FSO/RF混合链路相比单站可获得4~25 dB的增益.展开更多
依据互信息理论提出的互信息匹配识别模型MIM(Mutual Information Matching),能够有效地综合处理语音信号的统计分布特征与时变分布特征,并具有较强的鲁棒性。介绍了运用互信息进行说话人模式匹配的原理,探讨了基于文本的说话人识别中MI...依据互信息理论提出的互信息匹配识别模型MIM(Mutual Information Matching),能够有效地综合处理语音信号的统计分布特征与时变分布特征,并具有较强的鲁棒性。介绍了运用互信息进行说话人模式匹配的原理,探讨了基于文本的说话人识别中MIM模型的应用,通过说话人辨别实验对MIM模型的性能进行了实验分析,并与其它识别模型DTW和GMM进行了比较。对18名男性和12名女性组成的30名说话人进行的识别实验表明, MIM模型的说话人识别性能较好,在采用LPCC特征参数的情况下,平均错误识别率为1.33％。展开更多
基金Project supported by the National Natural Science Foundationof China (Nos. 61103010,61103190,and 60803100)the National Basic Research Program (973) of China (No. 2012CB933500)the High-Tech R&D Program (863) of China (No.2012AA011001)
文摘The error patterns of a wireless channel can be represented by a binary sequence of ones(burst) and zeros(run),which is referred to as a trace.Recent surveys have shown that the run length distribution of a wireless channel is an intrinsically heavy-tailed distribution.Analytical models to characterize such features have to deal with the trade-off between complexity and accuracy.In this paper,we use an independent but not identically distributed(inid) stochastic process to characterize such channel behavior and show how to parameterize the inid bit error model on the basis of a trace.The proposed model has merely two parameters both having intuitive meanings and can be easily figured out from a trace.Compared with chaotic maps,the inid bit error model is simple for practical use but can still be deprived from heavy-tailed distribution in theory.Simulation results demonstrate that the inid model can match the trace,but with fewer parameters.We then propose an improvement on the inid model to capture the 'bursty' nature of channel errors,described by burst length distribution.Our theoretical analysis is supported by an experimental evaluation.
基金supported by the National Key Scientific Instrument and Equipment Development Project(Grant No.2013YQ200607)China NSF Grants(Grant No.61631020)+2 种基金Aeronautical Science Foundation of China(Grant No.2017ZC52021)Fundamental Research Funds for the Central Universities(Grant No.NJ20160027)Open Foundation for Graduate Innovation of NUAA(Grant No.kfjj20160412 and kfjj20170405)
文摘In this paper, a multi-hop relay channel model based on unmanned aerial vehicles(UAVs) is established by taking into account of the propagation loss, shadowing, and multi-path fading. Based on the proposed channel model, the cascaded propagation loss of relay link and the cascaded probability density function(PDF) of channel fading are derived. Moreover, the theoretical performance of the UAV-based relay system, i.e., the outage probability, bit error rate(BER), and channel capacity, is also analysed and derived. Simulation results show agreement with theoretical results for the hill, mountain, and sea scenarios, indicating the accuracy of both the simulations and derivations.
文摘针对气象变化对自由空间光(Free Space Optical,FSO)通信链路和毫米波射频(Radio Frequency,RF)通信链路可用率的影响问题,采用马尔科夫建模与稳态概率求解计算方法,分析不同天气条件下FSO/RF混合链路的双接收站分集与中断概率性能.基于FSO链路和RF链路的信道模型,采用有限状态马尔科夫链(Finite State Markov Chain,FSMC)分别对单双站FSO/RF混合链路的切换选择进行建模,推导得出不同参数和天气情况下系统稳态的中断概率表达式.数值计算结果表明,当中断概率达到10^(-6),雨雾天气链路距离为1~7 km时,双站FSO/RF混合链路相比单站可获得4~25 dB的增益.
文摘依据互信息理论提出的互信息匹配识别模型MIM(Mutual Information Matching),能够有效地综合处理语音信号的统计分布特征与时变分布特征,并具有较强的鲁棒性。介绍了运用互信息进行说话人模式匹配的原理,探讨了基于文本的说话人识别中MIM模型的应用,通过说话人辨别实验对MIM模型的性能进行了实验分析,并与其它识别模型DTW和GMM进行了比较。对18名男性和12名女性组成的30名说话人进行的识别实验表明, MIM模型的说话人识别性能较好,在采用LPCC特征参数的情况下,平均错误识别率为1.33％。
