{"title":"马尔可夫衰落信道无线自组网的遍历空间吞吐量","authors":"Chun-Hung Liu, J. Andrews","doi":"10.1109/WIOPT.2011.5930042","DOIUrl":null,"url":null,"abstract":"Most work on wireless network throughput ignore the temporal correlation inherent to wireless channels, due to trouble with tractability. In order to better capture the temporal variations of wireless network throughput, this paper introduces the metric of ergodic spatial throughput (EST), which includes spatial and temporal ergodicity. All transmitters in the network form a stationary Poisson point process and all channels are modeled by a finite state Markov chain. The bounds on EST are characterized, and their scaling behaviors for a sparse and dense network are discussed. From these results, we show that the EST can be characterized by the inner product of the channel state vector and the invariant probability vector of the Markov chain. This indicates that channel-aware opportunistic transmission (CAOT) may not always increase the EST.","PeriodicalId":430755,"journal":{"name":"2011 International Symposium of Modeling and Optimization of Mobile, Ad Hoc, and Wireless Networks","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Ergodic spatial throughput of wireless ad hoc networks with Markovian fading channels\",\"authors\":\"Chun-Hung Liu, J. Andrews\",\"doi\":\"10.1109/WIOPT.2011.5930042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most work on wireless network throughput ignore the temporal correlation inherent to wireless channels, due to trouble with tractability. In order to better capture the temporal variations of wireless network throughput, this paper introduces the metric of ergodic spatial throughput (EST), which includes spatial and temporal ergodicity. All transmitters in the network form a stationary Poisson point process and all channels are modeled by a finite state Markov chain. The bounds on EST are characterized, and their scaling behaviors for a sparse and dense network are discussed. From these results, we show that the EST can be characterized by the inner product of the channel state vector and the invariant probability vector of the Markov chain. This indicates that channel-aware opportunistic transmission (CAOT) may not always increase the EST.\",\"PeriodicalId\":430755,\"journal\":{\"name\":\"2011 International Symposium of Modeling and Optimization of Mobile, Ad Hoc, and Wireless Networks\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Symposium of Modeling and Optimization of Mobile, Ad Hoc, and Wireless Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WIOPT.2011.5930042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Symposium of Modeling and Optimization of Mobile, Ad Hoc, and Wireless Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIOPT.2011.5930042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ergodic spatial throughput of wireless ad hoc networks with Markovian fading channels
Most work on wireless network throughput ignore the temporal correlation inherent to wireless channels, due to trouble with tractability. In order to better capture the temporal variations of wireless network throughput, this paper introduces the metric of ergodic spatial throughput (EST), which includes spatial and temporal ergodicity. All transmitters in the network form a stationary Poisson point process and all channels are modeled by a finite state Markov chain. The bounds on EST are characterized, and their scaling behaviors for a sparse and dense network are discussed. From these results, we show that the EST can be characterized by the inner product of the channel state vector and the invariant probability vector of the Markov chain. This indicates that channel-aware opportunistic transmission (CAOT) may not always increase the EST.