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水声通信信道中的OPNET建模与仿真 被引量:4
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作者 Dao Van Phuong 左加阔 +2 位作者 bui thi oanh 方世良 赵力 《东南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2014年第3期477-481,共5页
针对水声通信网络信道的实现开销大、复杂性高的特点,提出了一种能够仿真分析水声通信网络的有效方法.该方法分别使用OPNET中的Propagation-Delay-Stage,Receiver-Power-Stage和Background-Noise-Stage三个工具来仿真水声信道中的传播... 针对水声通信网络信道的实现开销大、复杂性高的特点,提出了一种能够仿真分析水声通信网络的有效方法.该方法分别使用OPNET中的Propagation-Delay-Stage,Receiver-Power-Stage和Background-Noise-Stage三个工具来仿真水声信道中的传播延迟、发射机功率和水声噪声(水声噪声包括紊流、船运、风波和热噪声).其中,Propagation-Delay-Stage采用MacKenzie速度模型;Receiver-Power-Stage中有Thorp,Schulkin&Marsh和Francois&Garrison 3种传播损失模型.在该方法中,首先仿真比较了取不同传播损失模型时的水声信道,然后根据仿真结果选择一个合适的水声信道,并采用MACAW协议来仿真水声通信网络.最后,通过仿真实验对整个水声通信网络的吞吐量、误码率、丢包率进行了分析.实验结果表明,采用该方法能够有效地仿真水声通信网络. 展开更多
关键词 水声信道 OPNET 仿真 介质访问控制协议
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NBP-based localization algorithm for wireless sensor networks in NLOS environments
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作者 bui thi oanh 徐平平 +1 位作者 朱文祥 武贵路 《Journal of Southeast University(English Edition)》 EI CAS 2016年第4期395-401,共7页
To mitigate the impacts of non-line-of-sight(NLOS) errors on location accuracy, a non-parametric belief propagation(NBP)-based localization algorithm in the NLOS environment for wireless sensor networks is propose... To mitigate the impacts of non-line-of-sight(NLOS) errors on location accuracy, a non-parametric belief propagation(NBP)-based localization algorithm in the NLOS environment for wireless sensor networks is proposed.According to the amount of prior information known about the probabilities and distribution parameters of the NLOS error distribution, three different cases of the maximum a posterior(MAP) localization problems are introduced. The first case is the idealized case, i. e., the range measurements in the NLOS conditions and the corresponding distribution parameters of the NLOS errors are known. The probability of a communication of a pair of nodes in the NLOS conditions and the corresponding distribution parameters of the NLOS errors are known in the second case. The third case is the worst case, in which only knowledge about noise measurement power is obtained. The proposed algorithm is compared with the maximum likelihood-simulated annealing(ML-SA)-based localization algorithm. Simulation results demonstrate that the proposed algorithm provides good location accuracy and considerably outperforms the ML-SA-based localization algorithm for every case. The root mean square error(RMSE)of the location estimate of the NBP-based localization algorithm is reduced by about 1. 6 m in Case 1, 1. 8 m in Case 2 and 2. 3 m in Case 3 compared with the ML-SA-based localization algorithm. Therefore, in the NLOS environments,the localization algorithms can obtain the location estimates with high accuracy by using the NBP method. 展开更多
关键词 non-line-of-sight(NLOS) localization accuracy wireless sensor networks
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