接近香农限的编织卷积码设计与仿真

本文主要阐述了斜纹编织卷积码的编码结构、迭代译码以及活性距离和交织器对其误码性能的影响等基本概念。通过系统仿真,在AWGN信道下发现斜纹编织卷积码的系统性能与系统传输帧长和编码器个数都有很大的联系,其误码性能十分接近香农限,且没有错误地板效应。     

无线传感器网络中有效的安全数据融合机制

在无线传感器网络中,数据融合是实现有效传输和节省能源的一个重要途径,许多应用都需要可靠并且可信的数据来进行融合.针对上述要求,提出了一个新的安全数据融合算法来保证融合数据的机密性和完整性.算法使用端到端加密和逐跳加密相结合的方式进行数据传输,通过认证过程进行恶意节点及伪造数据的检测.仿真表明,提出的算法能够有效地检测出恶意节点,并保证融合结果的准确性.     

基于编织卷积码的增强型FM-DCSK系统的设计与仿真

FM-DCSK,即调频-差分相干混沌相移键控,是一种针对移动通信中的多径环境提出的调制解调方式,它以高频混沌信号作为载波,采用非相干解调,对对抗多径衰落有很好的效果。若将它用于无线通信中,将提高信道利用率,从而获得一定的经济效益。为了进一步提高其抗干扰和抗衰减性能,我们提出了加入信道编码与之结合的算法,发现性能有了大幅度的提高。该技术的提出对进一步推动混沌通信系统的研究和应用有重要意义。     

编织码编码原理及其分类

编织码 ( Woven码 )是一类包容性极强的新型高效纠错码 ,它是在级联码的基础上形成的 ,其编码结构具有把各类成员码按编织状组合编码的特点且其性能优于传统的 Turbo码。本文在简要阐述编织码的三种基本编码原理基础上对外经结构的不同编码方案构成的编织码做了简单的分类 ,这对优化设计和分析编织码性能具有积极推动作用。     

基于加权信任优化的传感器网络安全实现

In this paper, an optimized malicious nodes detection algorithm, based on Weighted Confidence Filter (WCF), is proposed to protect sensor networks from attacks. In this algorithm, each cluster head in a cluster-based hierarchical network figures out an average confidence degree by means of messages from its child nodes. The cluster head only accepts a message from the child node whose confidence degree is higher than the average. Meanwhile, it updates the confidence degrees for each of its child nodes by comparing the aggregation value and the received messages, and regards them as the weight of exactness of messages from nodes. A sensor node is judged to be malicious if its weight value is lower than the predefined threshold. Comparative simulation results verify that the proposed WCF algorithm is better than the Weighted Trust Evaluation (WTE) in terms of the detection ratio and the false alarm ratio. More specifically, with the WCF, the detection ratio is significantly improved and the false alarm ratio is observably reduced, especially when the malicious node ratio is 0.25 or greater. When 40% of 100 sensors are malicious, the detection accuracy is above 90% and the false alarm ratio is nearly only 1.8% .