II-NEW: Scalable Software Defined Radio Network Testbed for Hybrid Measurement and Emulation

II-新：用于混合测量和仿真的可扩展软件定义无线电网络测试台

基本信息

批准号：
1730140
负责人：
Kapil Dandekar
金额：
$ 85万
依托单位：
Drexel University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1730140&HistoricalAwards=false
关键词：
II NEW Scalable Software Defined

项目摘要

Recent advancements in wireless network protocols offer opportunities in new research areas including algorithm design, spectrum optimization, throughput maximization, and wireless security. Each time wireless technologies evolve, additional testing and certification steps are required, and, in most cases, several rounds of such verification are needed. These steps are crucial to ensure the final product is indeed ready for public use. Wireless protocol and algorithm developers leverage highly-customizable software defined radio (SDR) nodes to create and improve their design. Although SDRs offer an ideal environment for testing using point-to-point wireless links, they incur an increased overhead to the user for when a large-scale network measurements involving multiple radios are required. At present, there does not exist, a remotely accessible testbed that would allow users to customize SDR applications and test their radios with controllable radio propagation (emulated, simulated, and over-the-air) channels. The testbed resulting from this project will achieve this goal, and in doing so, establish Drexel University as a leader in cybersecurity and telecommunication systems research. Upon completion of the project, the equipment will be locally and remotely shared with faculty, staff, and students in the research community for educational purposes.The testbed will consist of Ettus USRP SDR nodes (i.e. N210, X310) connected to an RFNest 16-port Wireless Channel Emulator from Intelligent Automation, Inc., which offers capabilities of providing highly controlled wireless environments for repeatable experiments. A hardware infrastructure will be developed to distribute radio frequency and timing cabling as well as to install these nodes on a ceiling scaffolding grid structure in Drexel's new laboratory space. A software infrastructure will be developed to allow for researchers to utilize the testbed for customized experiments involving emulated, simulated, and over-the-air wireless channels, where this unique combination of features have never been offered before. This infrastructure will require custom application programming interfaces (for interfacing with the SDRs, RFNest, host computers, and switches) and remote access interfaces (web GUI, ssh) to allow users to upload their custom hardware and software designs. By leveraging existing software platforms, the project will offer sophisticated experiment setup, measurement and data management tools as well as emulated network options. To add to the unique features of the testbed, Drexel's software defined communications (SDC) testbed, which offers on-the-fly scalability, will be ported to X310s and made available as a part of the project.

无线网络协议的最新进展为新的研究领域提供了机会，包括算法设计、频谱优化、吞吐量最大化和无线安全。每次无线技术的发展，都需要额外的测试和认证步骤，并且在大多数情况下，需要多轮此类验证。这些步骤对于确保最终产品确实可供公众使用至关重要。无线协议和算法开发人员利用高度可定制的软件定义无线电 (SDR) 节点来创建和改进其设计。尽管 SDR 为使用点对点无线链路进行测试提供了理想的环境，但当需要进行涉及多个无线电的大规模网络测量时，它们会增加用户的开销。目前，尚不存在可远程访问的测试台，允许用户定制 SDR 应用程序并使用可控无线电传播（仿真、模拟和无线）通道测试其无线电。该项目产生的测试平台将实现这一目标，并在此过程中使德雷塞尔大学成为网络安全和电信系统研究的领导者。该项目完成后，设备将在本地和远程与研究社区的教职员工和学生共享，用于教育目的。测试平台将由连接到 RFNest 16-的 Ettus USRP SDR 节点（即 N210、X310）组成。来自Intelligent Automation, Inc.的端口无线通道仿真器，它能够为可重复的实验提供高度受控的无线环境。将开发硬件基础设施来分配射频和定时布线，并将这些节点安装在德雷克塞尔新实验室空间的天花板脚手架网格结构上。将开发一个软件基础设施，允许研究人员利用该测试台进行涉及仿真、模拟和无线无线通道的定制实验，这种独特的功能组合以前从未提供过。该基础设施将需要定制应用程序编程接口（用于与 SDR、RFNest、主机和交换机连接）和远程访问接口（Web GUI、ssh），以允许用户上传其定制硬件和软件设计。通过利用现有的软件平台，该项目将提供复杂的实验设置、测量和数据管理工具以及模拟网络选项。为了增加测试台的独特功能，Drexel 的软件定义通信 (SDC) 测试台提供即时可扩展性，将被移植到 X310 并作为项目的一部分提供。

项目成果

期刊论文数量（19）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Radio Modulation Classification Using Deep Residual Neural Networks

DOI：
10.1109/milcom55135.2022.10017640
发表时间：
2022-11
期刊：
MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)
影响因子：
0
作者：
Adeeb Abbas;Vasil Pano;G. Mainland;K. Dandekar
通讯作者：
Adeeb Abbas;Vasil Pano;G. Mainland;K. Dandekar

Securing Wireless Communication via Hardware-Based Packet Obfuscation

通过基于硬件的数据包混淆保护无线通信

DOI：
10.1007/s41635-019-00070-0
发表时间：
2019
期刊：
Journal of Hardware and Systems Security
影响因子：
0
作者：
Chacko, James;Juretus, Kyle;Jacovic, Marko;Sahin, Cem;Kandasamy, Nagarajan;Savidis, Ioannis;Dandekar, Kapil R.
通讯作者：
Dandekar, Kapil R.

Mitigating RF jamming attacks at the physical layer with machine learning

通过机器学习减轻物理层的射频干扰攻击