Cognitive Radio Networks with Wireless Sensor Applications

具有无线传感器应用的认知无线电网络

• 批准号: RGPIN-2016-04038
• 负责人: Fernando, Xavier
• 金额: $ 2.62万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 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=708968
• 关键词: Cognitive; Radio; Networks; Wireless; Sensor

Wireless sensor networks (WSNs), part of the fast emerging Internet of Things will be playing vital role in transforming our lives. Potentially huge number of these sensors will soon be deployed to perform simple to complex tasks such as automatically controlling heat and light in smart homes to guiding autonomous vehicles and missiles. Finding adequate radio spectrum of these potentially numerous wireless sensors is a major issue. While Industry Canada is struggling to allocate more frequency bands, up to mm wave bands, many researchers' experimental studies show that already allocated spectrum is typically underused by 25-30%. Cognitive radio (CR) networks are a new form of intelligent wireless network where, the cognitive (secondary) users are configured to coexist with licensed (primary) users without causing harmful electromagnetic interference to them by opportunistic spectrum access. There are a few steps in the successful implementation of a CR cycle. Namely, spectrum awareness (achieved through sensing various spectrum parameters and spectrum occupancy), analysis and decision making based on the observation, and spectrum exploitation (adaptation). These basic functions need to be carried out repeatedly in a cognitive radio network. Another challenge in WSN is providing energy. Battery management and maintenance of these sensors can be a prohibitively expensive exercise because of their abundance. Sensors' performance will deteriorate with the remaining energy level and dead sensor nodes will affect the performance of an entire network, especially in multi-hop networks. Improper battery disposal will also cause environmental pollution and health hazardous in the long run. The energy issue can be alleviated by energy harvesting. The ambience has energy in the forms of light, heat, mechanical vibrations and electromagnetic radiations. Especially, cognitive WSN can harvest energy from the primary network. This energy has to be collected with appropriate transducers, stored reliably and used for wireless data transmission w

无线传感器网络（WSN），快速的一部分 新兴的物联网将在改变我们的 生命。这些传感器的可能很快将被部署到 执行简单至复杂的任务，例如自动控制热量和 在智能家园中点亮，以指导自动驾驶汽车和导弹。发现 这些潜在众多无线传感器的足够无线电谱是一个 主要问题。而加拿大工业公司正在努力分配更多的频率 乐队，最多可MM波带，许多研究人员的实验研究表明， 已经分配的频谱通常不足25-30％。 认知无线电（CR）网络是一种新形式 智能无线网络，认知（次要）用户是 配置为与许可（主要）用户共存而不引起有害 电磁干扰通过机会频谱访问。那里 是成功实施CR周期的几步。即， 频谱意识（通过感知各种频谱参数而实现 频谱占用），基于观察的分析和决策，以及 频谱开发（适应）。这些基本功能需要携带 在认知无线网络中反复出现。 WSN中的另一个挑战是提供能源。 这些传感器的电池管理和维护可能是一个过时的 昂贵的锻炼，因为它们的丰富性。传感器的性能将 剩余能量水平和死传感器节点的恶化会影响 整个网络的性能，尤其是在多跳网络中。 电池处置不当也会导致环境污染和健康 从长远来看危险。 能源问题可以通过能源缓解 收获。氛围具有光，热，机械形式的能量 振动和电磁辐射。特别是，认知WSN可以收获 主要网络的能量。必须收集这种能量 适当的传感器，可靠存储并用于无线数据 变速器w