基于Monte Carlo方法的任意概率密度随机数字信号发生器设计

在信号处理和计算机微观模拟的过程中,经常要构造具有特定概率密度的随机数发生器.采用常规方法实现难度较大且不具普遍性,本文根据Monte Carlo方法基本原理和随机信号的数字特征给出一种任意概率密度随机数发生器的设计方法及核心源代码.实验证明该方法简单高效、通用性好.     

信号检测中存储控制模块的FPGA设计及实现

文中从MSK跳频信号检测中存储控制模块的FPGA实现入手,分析了如何从存有信号和噪声的存储器中读出一段需要的数据,给出了其FPGA实现方法,并对该方法在实现中所用到的技巧及其在其他领域所具有的适用性作了说明.     

最大似然准则下的随机信号非重构压缩检测与分析

压缩采样能够较好的保持原信号的结构和信息,可以在不重构原信号条件下,直接处理采样值实现对原信号的检测。已有的信号压缩检测技术只对确知信号有效,而实际中信号多为随机信号。本文在建立基于非重构压缩采样的信号检测模型的基础上,详细推导了随机信号的最大似然检测算法,并在此基础上分析了算法的检测性能。理论分析与仿真结果表明:在虚警概率一定的条件下,检测概率随压缩比的减小呈对数增加,并且能够在获得高检测概率的同时保持较低的虚警概率;最后进一步验证了算法适用于宽带信号的检测。      

具有空间、时间双重分布性的随机会话密钥分发系统

本文首先提出了分布式密码协议的空间分布性和时间分布性的观点,并从双重分布性的角度研究分布式密码协议.作为一个例子,在V.Daza的密钥分发系统中一个只具有空间分布性的分布式密钥分发系统的基础上,引入了前置安全(proactive security)体制,得到了一个具有空间和时间双重分布性,可以抵抗动态攻击者的分布式密钥分发协议.拓展了分布式密码协议的研究空间.同时,文中在建立概率空间的基础上,证明了分布式密钥分发系统的安全性.     

Modeling and performance analysis of VI‐CRA: A congestion control algorithm for vehicular networks

This study proposes a Vehicle ID‐based CAM Rate Adaptation (VI‐CRA) algorithm for beacon messages in the vehicular network. Foremost, an improved vehicle ID–based analytical model is proposed at the MAC layer of vehicular network. The model weighs the random back‐off number chosen by vehicles participating in the back‐off process, with the vehicle ID incorporated in their respective CAMs. This eventually leads to the selection of a vehicle ID–based random back‐off number, minimizing the probability of collision due to same back‐off number selection. It is worth noting that the improved analytical model outperforms the existing works in terms of average packet delay since only one fourth of the contention window size is used throughout the simulation. To enhance the performance of the analytical model, the paper incorporates a congestion control algorithm, by adapting the rate of CAM broadcast over the control channel. The algorithm is designed considering a wide range of scenarios, ranging from nonsaturated to extremely saturated network (in terms of collision probability) and sparsely distributed to teemed network (in terms of vehicular density). For better analyses of simulation results, the algorithm is applied over different vehicle ID–based back‐off numbers. Simulation results for all the back‐off numbers show that vehicle ID–based CAM rate adaptation algorithm performs better than the traditional fixed CAM rate IEEE 802.11p, even at high vehicular density.     

Analysis and Optimization of an Adaptive Selective-Repeat Scheme for Time-Varying Channels with Feedback Errors

In this article, an adaptive SR ARQ scheme is analyzed and optimized in a time-varying channel environment with unreliable feedback. Two-state Markov models are assumed for both the forward and the returnchannel.This enables the time behaviour of the entire system to be modelledby a Markov chain. To have an easy-to-implement scheme, we choose the smaller packet size to be half of the bigger one. Thus, there is only oneindependent design parameter related to packet size. The other two parametersare associated with channel sensing. The performance of the adaptive schemeis measured by its average throughput, which is upper-bounded by the throughput of the so-called ideal adaptive scheme. This upper bound is very useful in the optimization of the packet size and other design parameters. From the results, it can be concluded that the selection of the packet size is at least as critical as the optimization of the other parameters. The feedback errors degrade the throughput of the scheme, but their effect on the parameter optimization turns out to be almost negligible.