Efficient Algorithms for Cognitive Radio Networks

认知无线电网络的高效算法

• 批准号: RGPIN-2018-05523
• 负责人: AbdelRaheem, Esam
• 金额: $ 1.68万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=643313
• 关键词: Efficient; Algorithms; Cognitive; Radio; Networks

Cognitive radio (CR) is a radio with an intelligent layer of awareness and learning necessary to achieve optimal performance under dynamic and unpredictable conditions. CR can dynamically adapt its behavior, through its awareness, to the radio environment and spectrum policy. One of the most critical components of CR technology is spectrum sensing (SS). By sensing and adapting to the environment, a CR is able to fill in spectrum holes and serve secondary users without harmful interference to the primary users. SS techniques can be categorized into two categories: local SS, and collaborative SS (CSS). There are three main local techniques which are: matched filter detection technique, energy detection technique, and cyclostatinary detection. CSS significantly alleviates the deterioration of sensing performance due to destructive radio conditions. Software-defined radio (SDR) is a key enabling technology to realize CRs. ******The proposal considers improved algorithms for CR Networks (CRNs). The proposal will investigate efficient blind SS/CSS techniques that would lead to decrease sensing time while improving the probability of detection; overhead compromise will be considered. The proposal will also investigate cluster-based SS (CBSS) approaches for CRNs that would maintain high performance under noise uncertainty, low signal-to-noise-ratio (SNR) conditions, and multipath fading conditions. Scenarios, where more than one primary user exists, will be investigated and analyzed. Performance enhancement of local SS using adaptive joint sensing threshold and sensing time will be investigated as well as enhancing energy efficiency for wideband CSS in CRNs using coalitional game theory.******Vehicular ad hoc network (VANET) is on the rise due to increasing demands for vehicles to communicate with each other and with the infrastructure to ensure road safety and to introduce new services. The proposal considers efficient solutions for CR-VANETs that would consider sensing the spectrum, forming clusters while on the move. SS techniques under fast fading will be investigated to serve CR-VANET. Methods to protect the primary user (PU) in CR-VANET need to be investigated and developed. Efficient medium access control (MAC) schemes that would lead to enhance the sensing performance in CR VANET will be investigated. Investigating the impact of changing mobility parameters (high speed, changeable topology, etc.) on sensing performance and accuracy will be investigated. ***This proposal aims to provide a research environment where graduate and undergraduate students get involved in state-of-the-art topics in computer-communication networks that definitely will enhance their potential and knowledge.

认知无线电（CR）是一种具有智能感知和学习层的无线电，可在动态和不可预测的条件下实现最佳性能。CR可以通过其感知来动态地调整其行为以适应无线电环境和频谱策略。CR技术最关键的组成部分之一是频谱感知（SS）。通过感知和适应环境，CR能够填补频谱漏洞并为次要用户提供服务，而不会对主要用户造成有害干扰。SS技术可以分为两类：本地SS和协作SS（CSS）。主要有三种局部化技术：匹配滤波检测技术、能量检测技术和循环平稳检测技术。CSS显著地抑制了由于破坏性无线电条件而导致的感测性能的恶化。软件无线电（SDR）是实现CR的关键使能技术。** 该提案考虑了CR网络（CRN）的改进算法。该提案将调查有效的盲SS/CSS技术，这将导致减少感测时间，同时提高检测的概率;开销妥协将被考虑。该提案还将研究CRN的基于集群的SS（CBSS）方法，该方法将在噪声不确定性，低信噪比（SNR）条件和多径衰落条件下保持高性能。将调查和分析存在一个以上主要用户的情况。将研究使用自适应联合感知阈值和感知时间的本地SS的性能增强，以及使用联盟博弈论来提高CRN中宽带CSS的能量效率。**车辆自组织网络（VANET）正在崛起，由于日益增长的需求，车辆相互通信，并与基础设施，以确保道路安全和引入新的服务。该提案考虑了CR-VAN的有效解决方案，该方案将考虑感知频谱，在移动时形成集群。快衰落下的扩频技术将被研究用于CR-VANET。保护CR-VANET中的主用户（PU）的方法需要研究和开发。有效的媒体访问控制（MAC）计划，将导致提高感知性能的CR VANET将被调查。调查移动性参数（高速、可变拓扑等）变化的影响将调查传感性能和准确性。* 本提案旨在提供一个研究环境，让研究生和本科生参与计算机通信网络中最先进的主题，这肯定会提高他们的潜力和知识。