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（WSNs）是快速的一部分