{"title":"基于接收机的IEEE 802.11 ad-hoc网络跨层容量增强设计方法","authors":"Satish Y. Ket, R. Awale","doi":"10.1145/1980022.1980197","DOIUrl":null,"url":null,"abstract":"The performance of IEEE 802.11 with different network densities and protocol configurations is of interest, particularly in distributed coordination function (DCF) mode. A mathematical model for one hop network IEEE 802.11 protocol was introduced by Bianchi [2] to analytically derive the saturated throughput. Our ultimate goal is to enhance the capacity of Ad-hoc network closer to the analytical values of this model. As an attempt, we propose the Receiver Based Capacity Enhancement Algorithm using Cross-Layer Design Approach (RCECLD) by dynamically adapting the data rate. It uses Signal-to-Noise Ratio (SNR) values calculated by Physical layer and exported to Medium Access Control (MAC) layer via the cross-layer interface to estimate the prevailing channel state. In RCECLD the receiver decides the transmission data rate by calculating the SNR value of received RTS (Ready-to-Send), which is in turn an estimate of the prevailing channel state, and piggybacking it through CTS (Clear-to-Send) to the transmitter. Accordingly transmitter transmits the data frame with adopted data rate.\n The capacity of the Ad-hoc network is enhanced with RCECLD. It is investigated through an extensive set of simulations. The results indicate that the enhancement is very close to analytical values for smaller network size and it is about 2.5 times more than Auto-Rate Fallback (ARF) [8], in spite of fading and mobility effects.","PeriodicalId":197580,"journal":{"name":"International Conference & Workshop on Emerging Trends in Technology","volume":"232 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Receiver based capacity enhancement with cross-layer design approach for IEEE 802.11 ad-hoc networks\",\"authors\":\"Satish Y. Ket, R. Awale\",\"doi\":\"10.1145/1980022.1980197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The performance of IEEE 802.11 with different network densities and protocol configurations is of interest, particularly in distributed coordination function (DCF) mode. A mathematical model for one hop network IEEE 802.11 protocol was introduced by Bianchi [2] to analytically derive the saturated throughput. Our ultimate goal is to enhance the capacity of Ad-hoc network closer to the analytical values of this model. As an attempt, we propose the Receiver Based Capacity Enhancement Algorithm using Cross-Layer Design Approach (RCECLD) by dynamically adapting the data rate. It uses Signal-to-Noise Ratio (SNR) values calculated by Physical layer and exported to Medium Access Control (MAC) layer via the cross-layer interface to estimate the prevailing channel state. In RCECLD the receiver decides the transmission data rate by calculating the SNR value of received RTS (Ready-to-Send), which is in turn an estimate of the prevailing channel state, and piggybacking it through CTS (Clear-to-Send) to the transmitter. Accordingly transmitter transmits the data frame with adopted data rate.\\n The capacity of the Ad-hoc network is enhanced with RCECLD. It is investigated through an extensive set of simulations. The results indicate that the enhancement is very close to analytical values for smaller network size and it is about 2.5 times more than Auto-Rate Fallback (ARF) [8], in spite of fading and mobility effects.\",\"PeriodicalId\":197580,\"journal\":{\"name\":\"International Conference & Workshop on Emerging Trends in Technology\",\"volume\":\"232 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference & Workshop on Emerging Trends in Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1980022.1980197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference & Workshop on Emerging Trends in Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1980022.1980197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Receiver based capacity enhancement with cross-layer design approach for IEEE 802.11 ad-hoc networks
The performance of IEEE 802.11 with different network densities and protocol configurations is of interest, particularly in distributed coordination function (DCF) mode. A mathematical model for one hop network IEEE 802.11 protocol was introduced by Bianchi [2] to analytically derive the saturated throughput. Our ultimate goal is to enhance the capacity of Ad-hoc network closer to the analytical values of this model. As an attempt, we propose the Receiver Based Capacity Enhancement Algorithm using Cross-Layer Design Approach (RCECLD) by dynamically adapting the data rate. It uses Signal-to-Noise Ratio (SNR) values calculated by Physical layer and exported to Medium Access Control (MAC) layer via the cross-layer interface to estimate the prevailing channel state. In RCECLD the receiver decides the transmission data rate by calculating the SNR value of received RTS (Ready-to-Send), which is in turn an estimate of the prevailing channel state, and piggybacking it through CTS (Clear-to-Send) to the transmitter. Accordingly transmitter transmits the data frame with adopted data rate.
The capacity of the Ad-hoc network is enhanced with RCECLD. It is investigated through an extensive set of simulations. The results indicate that the enhancement is very close to analytical values for smaller network size and it is about 2.5 times more than Auto-Rate Fallback (ARF) [8], in spite of fading and mobility effects.