{"title":"Cognitive Scheduling and Resource Allocation for Space to Ground Communication","authors":"M. Koets, Justin Blount, Jarred Blount","doi":"10.1109/CCAAW.2019.8904914","DOIUrl":null,"url":null,"abstract":"This paper presents a mathematical model for a cognitive communication network applicable to satellite communications with ground stations. The model employs abstract elements to describe a communications network, allowing the approach to be applied to a wide range of real-world communications systems and problems. The model includes representation of communications paths, spacecraft capabilities, time-varying demand for data transfer, changes in visibility due to satellite motion, time-varying availability of channels, and regulatory constraints on the use of radio communication bands. These model elements permit the detailed description of the structure and constraints of a communications problem. The model establishes a formal definition for a communication schedule which assigns communications resources to specific communicators at specific times. The model also formalizes constraints on the interactions between communicators, establishing the definition of a valid schedule in which communications conflicts do not occur and the definition of a good schedule in which communications resources are used efficiently. The paper also presents a dynamic reasoning methodology which uses the model to allocate communications resources in response to changing network conditions and communications loads. Implementation of the reasoning process using Answer Set Programming is demonstrated, providing illustration of the practicality of the approach. The application of the model and methodology to an example satellite communication network is presented. Using this approach significantly improved performance with respect to static resource allocation is demonstrated.","PeriodicalId":196580,"journal":{"name":"2019 IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW)","volume":"401 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCAAW.2019.8904914","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a mathematical model for a cognitive communication network applicable to satellite communications with ground stations. The model employs abstract elements to describe a communications network, allowing the approach to be applied to a wide range of real-world communications systems and problems. The model includes representation of communications paths, spacecraft capabilities, time-varying demand for data transfer, changes in visibility due to satellite motion, time-varying availability of channels, and regulatory constraints on the use of radio communication bands. These model elements permit the detailed description of the structure and constraints of a communications problem. The model establishes a formal definition for a communication schedule which assigns communications resources to specific communicators at specific times. The model also formalizes constraints on the interactions between communicators, establishing the definition of a valid schedule in which communications conflicts do not occur and the definition of a good schedule in which communications resources are used efficiently. The paper also presents a dynamic reasoning methodology which uses the model to allocate communications resources in response to changing network conditions and communications loads. Implementation of the reasoning process using Answer Set Programming is demonstrated, providing illustration of the practicality of the approach. The application of the model and methodology to an example satellite communication network is presented. Using this approach significantly improved performance with respect to static resource allocation is demonstrated.