Cognitive Radio Networks with Wireless Sensor Applications

无线传感器网络(WSNs)是快速崛起的物联网的一部分，它将在改变我们的生活方面发挥至关重要的作用。数量巨大的这种传感器可能很快就会被部署到执行从简单到复杂的任务，比如自动控制智能家居中的热量和光线，以引导自动驾驶车辆和导弹。为这些潜在的众多无线传感器找到足够的无线电频谱是一个主要问题。虽然加拿大工业部正在努力分配更多的频率*频段，最高可达毫米频段，但许多研究人员的实验研究表明，*已经分配的频谱通常未得到充分利用25%-30%。*认知无线电(CR)网络是一种新型的*智能无线网络，其中认知(次要)用户*被配置为*与许可(主要)用户共存，而不会通过机会性频谱接入对他们造成*有害的*电磁干扰。成功实施CR周期有几个步骤。即，*频谱感知(通过感知各种频谱参数和*频谱占用实现)，基于观测的分析和决策，以及*频谱开发(适应)。这些基本功能需要在认知无线电网络中重复执行。无线传感器网络的另一个挑战是提供能量。这些传感器的电池管理和维护可能是一项昂贵得令人望而却步的工作，因为它们的数量很多。传感器的性能将随着剩余的能量水平而恶化，失效的传感器节点将影响*整个网络的性能，特别是在多跳网络中。*电池处理不当还会造成环境污染和健康*长期有害。*能源问题可以通过收集能源来缓解。大气具有光、热、机械振动和电磁辐射等形式的能量。特别是，认知型无线传感器网络可以从主网络中获取能量。这种能量必须用*适当的传感器收集，可靠地存储，并用于无线数据传输，这通常是突发的。能量收集过程的零星和不可靠的性质以及电子元件的特性必须被适当地建模以设计可行的能量收集无线传感器网络。*当频谱窃取CR功能被*添加到能量采集无线传感器中时，研究问题非常*具有挑战性。然而，由于迫在眉睫的必要性，调查这种情况是必要的。此外，未来的认知能量采集无线传感器网络仍然需要满足无线通信的传统要求，如适当的服务质量、满足延迟、吞吐量、公平性和可靠性。拟议的研究计划将聚焦于这一方向，调查认知无线传感器网络中的紧迫问题，并找到新的解决方案。*

**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 which is typically bursty. The sporadic and unreliable nature of*the energy harvesting process as well as characteristics of electronic elements*has to be appropriately modeled to design viable energy harvesting WSN. *** ***When the spectrum stealing CR functionality is*added to the energy harvesting wireless sensors, the research problem is very*challenging. However, it is essential to investigate this scenario due to the*pressing necessity. In addition, traditional requirements of wireless*communication such as appropriate quality of service, meeting latency,*throughput, fairness and reliability still have to be met by future cognitive*energy harvesting wireless sensor network. The proposed research program will*focus on this direction, investigating pressing issues in cognitive wireless*sensor networks and finding novel solutions. *** *** *** *** *** *** ******