作者：王力群1,2
作者单位：1. 四川大学计算机学院, 四川 成都 610064;
2. 南京铁道职业技术学院软件与艺术学院, 江苏 南京 210031
关键词：状态融合;小波变换;干扰影响;无线网络信号
摘要：
为解决无线网络信号在传输过程中由于受到其他信号的干扰,导致接收端接收的信号与原始信号相比存在误差的问题,该文在利用数据关联和卡尔曼滤波对信号进行融合(fusion method of signal filtering based on wavelet transform and Calman,FSWC)的基础上,利用FARIMA(p,d,q)模型和数据关联来建立一种新的信号融合算法(signal fusion based on wavelet transform and date association,SFTD).通过仿真实验分别研究融合信号与干扰距离、发送速率、容量、功率的变化情况.仿真结果表明:随着干扰距离的增加,容量开始呈现正相关趋势,直至趋于平稳,并且发送速率、容量、功率对融合信号也产生较大影响;SFTD算法比FSWC算法具有更好的信号状态融合准确性.
A new fusion method of signal state
WANG Liqun1,2
1. Sichuan University Computer College, Chengdu 610064, China;
2. Nanjing Railway Vocational and Technical College, Nanjing 210031, China
Abstract: In order to solve the wireless network signal in the transmission process due to interference by other signals, resulting in signal received by a receiving terminal compared with the original signal errors exist problems, this paper on the signal integration using data association and Calman filter (fusion method of signal filtering based on wavelet transform and Calman, FSWC) basis, put forward a new fusion method for signal state (signal fusion based on wavelet transform and date association, SFTD), the method of using FARIMA(p, d, q) model and data association to establish a new fusion algorithm of signal. Through the simulation experiment studied the changes of signal and interference distance, fusion rate, transmission capacity, power, the simulation results show that, with increasing interference distance, capacity is beginning to show positive correlation trend, until stable; and a transmission rate, capacity, power also has a great impact on the fusion signal; the simulation results also illustrate, signal state and the SFTD algorithm has better than the FSWC algorithm fusion accuracy.
Keywords: state fusion;wavelet transform;interference;wireless network signal
2015, 41(4): 89-93 收稿日期: 2014-9-21;收到修改稿日期: 2014-11-28
基金项目: 全国教育科学“十二五”规划教育部规划课题(FJB110092)国家自然科学基金(6107022905)江苏省轨道交通控制工程中心开放基金(KFJ1312)
作者简介: 王力群(1961-),男,江苏南京市人,副教授,硕士,研究方向为网络可靠性、软件架构.
参考文献
[1] 朱静宜,张亶. 无线网络信号衰退测量方法研究与仿真[J].计算机仿真,2013,1(5):102-105.
[2] 宋国荣,刘兴奇,王洋,等. 视觉化机器人远程监控系统的设计与实现[J]. 计算机测量与控制,2013,10(8):1672-1683.
[3] 王成,胡卫东,杜小勇,等. 稀疏子带的多频段雷达信号融合超分辨距离成像[J]. 电子学报,2006,6(6):2180-2189.
[4] Zheng G, Choo L, Wong K. Optimal cooperative jamming to enhance physical layer security using relays[J]. IEEE Transactions on Signal Processing,2011,59(3):1317-1322.
[5] Bisnikm, Abouzeidaa, Isleraa. Stochastic event capture using mobile sensors subject to a quality metric[J]. IEEE Trans on Robotics,2007,23(4):676-692.
[6] 孙佩刚,赵海,罗玎玎,等. 无线传感器网络链路通信质量测量研究[J]. 通信学报,2007,28(10):14-22.
[7] Couto D, Aguayo D, Chambers B A, et al. Performance of multihop wireless networks: shortest path is not enough[J]. ACM SIGCOMM Computer Communication Review,2003,33(1):83-88.
[8] 舒坚,刘琳岚,樊佑磊,等. 无感知分组丢失下的无线传感器网络链路质量评估模型[J]. 通信学报,2011,32(4):103-111.
[9] 李国华,李建中,高宏. Ε-近似和加权公平性保证的无线传感器网络拥塞控制算法[J]. 计算机学报,2011,34(11):2197-2210.
[10] Ramachandran I, Das A K, Roy s. Analysis of the contention access period of IEEE 802.15.4 MAC[J]. ACM Transactions on Sensor Networks,2007,3(1):70-77.
[11] Zhai H Q, Chen X, Fang Y G. Improving transport layer performance in multihop ad hoc networks by exploiting MAC layer information[J]. IEEE Transactions on Wireless Communication,2007,6(5):1692-1701.
[12] 段谟意. 基于卡尔曼滤波和数据关联的无线网络状态融合方法[J]. 计算机应用,2012,32(11):3112-3114.
[13] 段谟意. 基于FARIMA模型的无线网络状态融合方法[J].计算机工程与设计,2012,33(10):3743-3746.
[14] Li X Y. Multicast capacity of wireless Ad Hoc networks[J].IEEE/ACM Transactions on Networking,2009,17(3):950-962.
[15] He X, Yener A. Cooperation with an untrusted relay:a secrecy perspective[J]. IEEE Transactions on Information Theory,2010,5(10):2001-2005.
