Intelligent Tactical Wireless Networks for Challenging Environments

适用于充满挑战的环境的智能战术无线网络

• 批准号: 538896-2019
• 负责人: Kaddoum, Georges
• 金额: $ 40.28万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=699307
• 关键词: Intelligent; Tactical; Wireless; Networks; Challenging

In recent years, artificial intelligence (AI), enabled by machine learning (ML), has revolutionized many technologies and pushed their performance and intelligent capabilities beyond expectations. Consequently, new intelligent wireless solutions aiming to increase the robustness, reliability, throughput, and other feature of the wireless networks are emerging. These solutions are appealing to the tech-industry which is continuously seeking to design ground-breaking products that excel in every performance measure, especially when it comes to lives-saving technologies such as in fields of civil defense, security, emergency, and tactical missions. This project introduces ML to tactical wireless networks (TWN), a different form of commercial communication networks, which is characterized by its robustness in constantly changing tactical situations and varying environments, with no pre-existing infrastructure. The sensitive nature of TWN applications forces the companies to independently develop their own technologies to ensure that the security and reliability standards are uncompromised. Thus, the tactical communications industry is highly competitive and requires strong R&D efforts from companies to keep their products innovative and competitive. In this respect, the collaboration between Ultra Electronics TCS and ETS, with the aim of introducing the recent breakthroughs in ML to tactical communications, is vital to keep the company among the major players in the market. The long-term objective of this project is to develop a proactive, self-aware, self-adaptive, and predictive tactical wireless networks that exploit ML and optimization tools to automate its deployment, operations and subsequently enhance its performance in challenging environments. The envisioned approach for adding such intelligent capabilities to the TWN is designing novel ML schemes at three network levels, the node-level for environment classification, link-level for decisions between two nodes, and cluster-level for the MAC and routing decisions. This research project will contribute to consolidating the stature of Canada as a leader in AI and wireless nets.

近年来，机器学习（ML）启用的人工智能（AI）已彻底改变了许多技术，并将其性能和智能能力推向了期望之外。因此，旨在提高无线网络的鲁棒性，可靠性，吞吐量和其他功能的新型智能无线解决方案正在出现。这些解决方案吸引了技术行业，该技术行业不断寻求设计在每种绩效措施中出色的突破性产品，尤其是在挽救救世技术的情况下，例如在民防，安全，紧急和战术任务领域。 该项目将ML引入了战术无线网络（TWN），这是一种不同形式的商业通信网络，其特征是它在不断变化的战术情况和不同的环境中稳健性，而没有预先存在的基础架构。 TWN应用的敏感性迫使公司独立开发自己的技术，以确保安全和可靠性标准不妥协。因此，战术通信行业具有很高的竞争力，需要公司的强大研发努力，以保持其产品创新和竞争力。在这方面，Ultra Electronics TCS和ETS之间的合作是为了将ML最近的突破性引入战术通信，对使该公司成为市场主要参与者至关重要。 该项目的长期目标是开发一种积极的，自我意识，自适应和预测的战术无线网络，该网络利用ML和优化工具来自动化其部署，操作并随后在具有挑战性的环境中提高其性能。 在TWN中添加此类智能功能的设想方法是在三个网络级别设计新颖的ML方案，即环境分类的节点级别，两个节点之间的决策链接级，以及Mac的群集级别和路由决策。 该研究项目将有助于巩固加拿大作为AI和无线网的领导者的身材。