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: $ 13.43万
• 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: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=720620
• 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，以机器学习（ML）为基础的人工智能（AI）彻底改变了许多技术，其性能和智能能力超出了人们的预期。因此，旨在提高无线网络的稳健性、可靠性、吞吐量和其他功能的新智能无线解决方案正在出现。这些解决方案对科技行业很有吸引力，科技行业不断寻求设计在各项性能指标上都表现出色的突破性产品，特别是在民防、安全、紧急情况和战术任务等领域的救生技术方面。 。该项目将机器学习引入战术无线网络（TWN），这是一种不同形式的商业通信网络，其特点是在不断变化的战术情况和变化的环境中具有鲁棒性，并且无需预先存在的基础设施。 TWN 应用的敏感性迫使公司独立开发自己的技术，以确保安全性和可靠性标准不受影响。因此，战术通信行业竞争激烈，需要企业大力研发，以保持产品的创新性和竞争力。在这方面，Ultra Electronics TCS 和 ETS 之间的合作旨在将机器学习的最新突破引入战术通信，这对于保持该公司在市场上的主要参与者地位至关重要。该项目的长期目标是开发一种主动、自我意识、自适应和预测性的战术无线网络，利用机器学习和优化工具来自动化其部署、操作，并随后增强其在充满挑战的环境中的性能。为 TWN 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：用于环境分类的节点级别、用于两个节点之间决策的链路级别以及用于 MAC 和路由决策的集群级别。该研究项目将有助于巩固加拿大作为人工智能和无线网络领导者的地位。