Fault tolerant machine learning for nanoscale cognitive radio

We introduce a machine learning-based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanoscale implementation constraints; we do not describe all physical details but believe future physical implementation to be feasible. The system uses analog computation and consists of cyclostationary feature extraction and a radial basis function network for classification. We describe a model for nanoscale faults in the system, and simulate experimental performance and fault tolerance in recognizing WLAN signals, under different levels of noise and computational errors. The system performs well under expected non-ideal manufacturing and operating conditions.     

改进的证据理论在合作频谱感知中的应用

为了能够在认知无线电网络中有效、准确地检测出授权用户,提出了基于改进的证据理论的合作频谱感知方案设计方法.根据各个次用户对授权用户进行多次本地检测得出的时域DS融合结果,设计并改进融合顺序和融合结构,将多个时域DS融合结果送到融合中心进行空域DS融合,得到最终判决.在此基础上,给出了融合顺序、融合结构的改变对算法性能的...     

Faster Deterministic Communication in Radio Networks

We study the communication primitives of broadcasting (one-to-all communication) and gossiping (all-to-all communication) in known topology radio networks, i.e., where for each primitive the schedule of transmissions is precomputed based on full knowledge about the size and the topology of the network. We show that gossiping can be completed in time units in any radio network of size n, diameter D, and maximum degree Δ=Ω(log n). This is an almost optimal schedule in the sense that there exists a radio network topology, specifically a Δ-regular tree, in which the radio gossiping cannot be completed in less than units of time. Moreover, we show a schedule for the broadcast task. Both our transmission schemes significantly improve upon the currently best known schedules by Gąsieniec, Peleg, and Xin (Proceedings of the 24th Annual ACM SIGACT-SIGOPS PODC, pp. 129–137, 2005), i.e., a O(D+Δlog n) time schedule for gossiping and a D+O(log ³ n) time schedule for broadcast. Our broadcasting schedule also improves, for large D, a very recent O(D+log ² n) time broadcasting schedule by Kowalski and Pelc. A preliminary version of this paper appeared in the proceedings of ISAAC’06. F. Cicalese supported by the Sofja Kovalevskaja Award 2004 of the Alexander von Humboldt Stiftung. F. Manne and Q. Xin supported by the Research Council of Norway through the SPECTRUM project.     

On neighbor discovery in cognitive radio networks

A cognitive radio node is a radio device capable of operating over multiple channels. As a result, a network consisting of one or more cognitive radio nodes can adapt to varying channel availability in its geographical region by dynamically changing the channel (or channels) nodes are using for communication.     

GPS软件接收机的模块设计与信号处理

采用Zarlink公司的GP2015对GPS射频前端进行下变频处理,将得到的中频模拟信号转换成数字信号,结合DSP开发技术对中频数字信号进行捕获、跟踪与定位解算,用软件无线电的方法实现GPS软件接收机的模块设计与信号处理。实验结果表明,软件无线电思想能实现算法与软件的高度灵活性,可有效提高GPS接收机的信号处理能力与系统性能。     

基于FPGA小数内插的新型数字射频存储器设计

介绍了数字射频存储技术的基本原理及其实现结构,分析了影响其性能的各种因素.提出了基于FPGA小数内插的方法对传统数字射频存储器进行改进,在不提高系统工作时钟的条件下,试图提高回波模拟信号的距离精度,给出了改进后的数字射频存储器结构.经过实际系统测试,证明了改进后的数字射频存储器可有效提高雷达回波信号的距离精度,满足距离高分辨雷达的需求.     

一种联盟博弈频谱感知机制

为了在主用户具有异构性且认知用户处于多路径衰减、阴影效应等低感知性能的认知环境中,使认知用户公平有效地进行频谱感知,提出一种联盟博弈频谱感知机制,将频谱感知问题建模为效用不可转移的联盟博弈。首先,将认知用户划分成多个子联盟,根据头结点选取原则选出各个子联盟的头结点;其次,根据规则进行子联盟合并或分裂;最后,子联盟头结点利用“OR”规则进行数据融合,得到最终感知结果并广播给子联盟内的所有认知用户。仿真实现和性能评价结果表明,该机制具有好的性能。     

认知无线电网络信道选择机制

认知无线电网络通过动态频谱接入来提高无线频谱资源利用率,而节点目标信道选择的优劣直接决定了频谱接入性能的好坏. 本文首先综合考虑信道增益和空闲时间两种因素,设计以实现最大化系统容量的目标信道选择机制,然后引入信道热度概念,提出一种多属性决策信道选择机制. 仿真结果表明,多属性决策信道选择机制在系统吞吐量和频谱利用率性能上都有明显的提高.     

化工设备巡检系统

为解决化工企业传统的人工设备巡检模式中存在的数据遗漏和效率低下等问题,在分析了业务流程的基础上,采用RFID技术为主要的数据采集技术,设计并实现了一个化工设备巡检系统．该系统采用J2EE四层体系框架,实现业务逻辑和数据分离．使用该系统可以高效、方便地完成对化工企业设备的巡检和维护管理．