{"title":"认知无线电网络中整合传感与传输的评估框架","authors":"","doi":"10.1016/j.compeleceng.2024.109708","DOIUrl":null,"url":null,"abstract":"<div><div>Cognitive radio technology provides a potential solution to the growing demand for radio spectrum resources. However, evaluating the differences between channel theoretical models in various application scenarios is a complex and critical challenge in cognitive radio technology. To address this issue, the authors propose a framework for evaluating performance that integrates spectrum sensing, allocation, and data transmission, and a mathematical derivation of how the parts are connected is given. The framework is capable of analyzing the sensing and transmission performance of different fading channel models. It enables the assessment of transmission performance for each heterogeneous secondary user (SU) across various transmission environments and decision thresholds, including parameters such as throughput, queue length, and packet rejection rate. Additionally, a performance metric is proposed to measure the impact of fading channel models on the primary user (PU). The simulation results show that the quantitative performance difference between the Rayleigh channel model and its improved Nakagami channel model in different environments can be obtained using the proposed evaluation framework. The proposed framework can improve the reliability and effectiveness of implementing cognitive radio networks in cross-application scenarios.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":4.0000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An evaluation framework integrating sensing and transmission in cognitive radio networks\",\"authors\":\"\",\"doi\":\"10.1016/j.compeleceng.2024.109708\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Cognitive radio technology provides a potential solution to the growing demand for radio spectrum resources. However, evaluating the differences between channel theoretical models in various application scenarios is a complex and critical challenge in cognitive radio technology. To address this issue, the authors propose a framework for evaluating performance that integrates spectrum sensing, allocation, and data transmission, and a mathematical derivation of how the parts are connected is given. The framework is capable of analyzing the sensing and transmission performance of different fading channel models. It enables the assessment of transmission performance for each heterogeneous secondary user (SU) across various transmission environments and decision thresholds, including parameters such as throughput, queue length, and packet rejection rate. Additionally, a performance metric is proposed to measure the impact of fading channel models on the primary user (PU). The simulation results show that the quantitative performance difference between the Rayleigh channel model and its improved Nakagami channel model in different environments can be obtained using the proposed evaluation framework. The proposed framework can improve the reliability and effectiveness of implementing cognitive radio networks in cross-application scenarios.</div></div>\",\"PeriodicalId\":50630,\"journal\":{\"name\":\"Computers & Electrical Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Electrical Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0045790624006359\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Electrical Engineering","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0045790624006359","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
An evaluation framework integrating sensing and transmission in cognitive radio networks
Cognitive radio technology provides a potential solution to the growing demand for radio spectrum resources. However, evaluating the differences between channel theoretical models in various application scenarios is a complex and critical challenge in cognitive radio technology. To address this issue, the authors propose a framework for evaluating performance that integrates spectrum sensing, allocation, and data transmission, and a mathematical derivation of how the parts are connected is given. The framework is capable of analyzing the sensing and transmission performance of different fading channel models. It enables the assessment of transmission performance for each heterogeneous secondary user (SU) across various transmission environments and decision thresholds, including parameters such as throughput, queue length, and packet rejection rate. Additionally, a performance metric is proposed to measure the impact of fading channel models on the primary user (PU). The simulation results show that the quantitative performance difference between the Rayleigh channel model and its improved Nakagami channel model in different environments can be obtained using the proposed evaluation framework. The proposed framework can improve the reliability and effectiveness of implementing cognitive radio networks in cross-application scenarios.
期刊介绍:
The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency.
Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.