{"title":"基于能量感知技术的认知甚高频陆地移动无线电通信网络频谱感知","authors":"Godfrey Niringiye, I. Oteyo, T. Bulega","doi":"10.1109/africon51333.2021.9570941","DOIUrl":null,"url":null,"abstract":"The 2015 migration from Very High Frequency (VHF) Analog to Digital Television (TV) created plenty of white spaces in the entire VHF TV Band (174–230 MHz). These white spaces can be used by other wireless applications and internet services whose radio spectrum is already pushed to maximum utilization and is therefore scarce for emerging wireless applications such as IP Television, high-speed wireless internet, cellular telephony, multimedia services, Zigbee, WiMax-Advanced. In this study, we implemented a VHF Land Mobile Radio System (LMRS) that can utilise the Television White Spaces (TVWS) in the upper VHF TV band for mission critical voice transmissions. We detected VHF Land Mobile Radio (LMR) transmissions in the TVWS using energy sensing techniques, with the real-time energy detector developed on the Software-Defined Radio (SDR) testbed composed of RTL-SDR device, VHF Radio and GNU Radio. We used a simulated energy detector using GNU Radio to set the evaluation benchmark. In both, the simulations and the real-time platform, a Narrow Band Frequency Modulation (NBFM) was generated and transmitted through the TVWS. The performance of the implemented real-time energy detector compared to the simulated one was lower, due to the noise distribution being not perfectly Additive White Gaussian Noise (AWGN), and thermal noise from the RTL-SDR. In addition, the transmission in TVWS was high in signal energy compared to transmission in traditional LMR frequency (approximately 10% improvement), and thus improved penetration in remote areas and thick forests.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Spectrum Sensing for Cognitive VHF Land Mobile Radio Communication Networks Using Energy Sensing Techniques\",\"authors\":\"Godfrey Niringiye, I. Oteyo, T. Bulega\",\"doi\":\"10.1109/africon51333.2021.9570941\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The 2015 migration from Very High Frequency (VHF) Analog to Digital Television (TV) created plenty of white spaces in the entire VHF TV Band (174–230 MHz). These white spaces can be used by other wireless applications and internet services whose radio spectrum is already pushed to maximum utilization and is therefore scarce for emerging wireless applications such as IP Television, high-speed wireless internet, cellular telephony, multimedia services, Zigbee, WiMax-Advanced. In this study, we implemented a VHF Land Mobile Radio System (LMRS) that can utilise the Television White Spaces (TVWS) in the upper VHF TV band for mission critical voice transmissions. We detected VHF Land Mobile Radio (LMR) transmissions in the TVWS using energy sensing techniques, with the real-time energy detector developed on the Software-Defined Radio (SDR) testbed composed of RTL-SDR device, VHF Radio and GNU Radio. We used a simulated energy detector using GNU Radio to set the evaluation benchmark. In both, the simulations and the real-time platform, a Narrow Band Frequency Modulation (NBFM) was generated and transmitted through the TVWS. The performance of the implemented real-time energy detector compared to the simulated one was lower, due to the noise distribution being not perfectly Additive White Gaussian Noise (AWGN), and thermal noise from the RTL-SDR. In addition, the transmission in TVWS was high in signal energy compared to transmission in traditional LMR frequency (approximately 10% improvement), and thus improved penetration in remote areas and thick forests.\",\"PeriodicalId\":170342,\"journal\":{\"name\":\"2021 IEEE AFRICON\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE AFRICON\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/africon51333.2021.9570941\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE AFRICON","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/africon51333.2021.9570941","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spectrum Sensing for Cognitive VHF Land Mobile Radio Communication Networks Using Energy Sensing Techniques
The 2015 migration from Very High Frequency (VHF) Analog to Digital Television (TV) created plenty of white spaces in the entire VHF TV Band (174–230 MHz). These white spaces can be used by other wireless applications and internet services whose radio spectrum is already pushed to maximum utilization and is therefore scarce for emerging wireless applications such as IP Television, high-speed wireless internet, cellular telephony, multimedia services, Zigbee, WiMax-Advanced. In this study, we implemented a VHF Land Mobile Radio System (LMRS) that can utilise the Television White Spaces (TVWS) in the upper VHF TV band for mission critical voice transmissions. We detected VHF Land Mobile Radio (LMR) transmissions in the TVWS using energy sensing techniques, with the real-time energy detector developed on the Software-Defined Radio (SDR) testbed composed of RTL-SDR device, VHF Radio and GNU Radio. We used a simulated energy detector using GNU Radio to set the evaluation benchmark. In both, the simulations and the real-time platform, a Narrow Band Frequency Modulation (NBFM) was generated and transmitted through the TVWS. The performance of the implemented real-time energy detector compared to the simulated one was lower, due to the noise distribution being not perfectly Additive White Gaussian Noise (AWGN), and thermal noise from the RTL-SDR. In addition, the transmission in TVWS was high in signal energy compared to transmission in traditional LMR frequency (approximately 10% improvement), and thus improved penetration in remote areas and thick forests.