Maryam Ahmadi, Jianping Pan, Lei Zheng, Lin X. Cai, Fei Tong
{"title":"Poster: geometrical distance distribution for modeling performance metrics in wireless communication networks","authors":"Maryam Ahmadi, Jianping Pan, Lei Zheng, Lin X. Cai, Fei Tong","doi":"10.1145/2639108.2642905","DOIUrl":null,"url":null,"abstract":"Geometrical distance distribution (GDD) between nodes in wireless communication networks plays a significant role in modeling network performance metrics. Existing work on obtaining GDD assumes the network geometry to be a regular one, such as circle and square. Due to the various complex effects of wireless signals, however, the network geometry usually is quite irregular. Therefore, this paper proposes a novel systematic and unified approach to obtain the GDD between two random nodes associated with arbitrary network geometries. To the best of our knowledge, this is the first work that will fill the gap in the literature of this field.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 20th annual international conference on Mobile computing and networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2639108.2642905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Geometrical distance distribution (GDD) between nodes in wireless communication networks plays a significant role in modeling network performance metrics. Existing work on obtaining GDD assumes the network geometry to be a regular one, such as circle and square. Due to the various complex effects of wireless signals, however, the network geometry usually is quite irregular. Therefore, this paper proposes a novel systematic and unified approach to obtain the GDD between two random nodes associated with arbitrary network geometries. To the best of our knowledge, this is the first work that will fill the gap in the literature of this field.