{"title":"无线局域网频谱使用的时域确定性-随机模型研究","authors":"K. Umebayashi, M. López-Benítez","doi":"10.1109/WCNC.2018.8377445","DOIUrl":null,"url":null,"abstract":"Duty cycle (DC) has been used to express the deterministic and stochastic aspects of spectrum usage. Specifically, a deterministic model for the mean of the duty cycle (MDC) has been proposed in a previous work. On the other hand, the observed DC (O-DC) during short time duration has randomness and a stochastic model is used to express the randomness. In this paper, we extend the conventional approach to a combined deterministic-stochastic (DS) model which represents both the deterministic and stochastic aspects. For the distribution of the O-DC, the beta distribution has been used as stochastic model, but we employ a mixture of beta distributions. The mixture-beta distribution can achieve higher accuracy but requires more capacity for data storage in spectrum usage measurements since it has a higher number of parameters than the beta distribution. For this issue, we employ regression analysis in DS-model to reduce the number of parameters while retaining the accuracy. We show the validity of DS-model based on exhaustive spectrum measurements in IEEE 802.11-based wireless local area networks.","PeriodicalId":360054,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"505 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A study on time domain deterministic-stochastic model of spectrum usage in WLAN\",\"authors\":\"K. Umebayashi, M. López-Benítez\",\"doi\":\"10.1109/WCNC.2018.8377445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Duty cycle (DC) has been used to express the deterministic and stochastic aspects of spectrum usage. Specifically, a deterministic model for the mean of the duty cycle (MDC) has been proposed in a previous work. On the other hand, the observed DC (O-DC) during short time duration has randomness and a stochastic model is used to express the randomness. In this paper, we extend the conventional approach to a combined deterministic-stochastic (DS) model which represents both the deterministic and stochastic aspects. For the distribution of the O-DC, the beta distribution has been used as stochastic model, but we employ a mixture of beta distributions. The mixture-beta distribution can achieve higher accuracy but requires more capacity for data storage in spectrum usage measurements since it has a higher number of parameters than the beta distribution. For this issue, we employ regression analysis in DS-model to reduce the number of parameters while retaining the accuracy. We show the validity of DS-model based on exhaustive spectrum measurements in IEEE 802.11-based wireless local area networks.\",\"PeriodicalId\":360054,\"journal\":{\"name\":\"2018 IEEE Wireless Communications and Networking Conference (WCNC)\",\"volume\":\"505 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Wireless Communications and Networking Conference (WCNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNC.2018.8377445\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Wireless Communications and Networking Conference (WCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC.2018.8377445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A study on time domain deterministic-stochastic model of spectrum usage in WLAN
Duty cycle (DC) has been used to express the deterministic and stochastic aspects of spectrum usage. Specifically, a deterministic model for the mean of the duty cycle (MDC) has been proposed in a previous work. On the other hand, the observed DC (O-DC) during short time duration has randomness and a stochastic model is used to express the randomness. In this paper, we extend the conventional approach to a combined deterministic-stochastic (DS) model which represents both the deterministic and stochastic aspects. For the distribution of the O-DC, the beta distribution has been used as stochastic model, but we employ a mixture of beta distributions. The mixture-beta distribution can achieve higher accuracy but requires more capacity for data storage in spectrum usage measurements since it has a higher number of parameters than the beta distribution. For this issue, we employ regression analysis in DS-model to reduce the number of parameters while retaining the accuracy. We show the validity of DS-model based on exhaustive spectrum measurements in IEEE 802.11-based wireless local area networks.