Kang Gao, N. Estes, B. Hochwald, J. Chisum, J. N. Laneman
{"title":"Power-performance analysis of a simple one-bit transceiver","authors":"Kang Gao, N. Estes, B. Hochwald, J. Chisum, J. N. Laneman","doi":"10.1109/ITA.2017.8023454","DOIUrl":null,"url":null,"abstract":"We analyze a one-bit wireless transceiver whose architecture is simple enough that its power versus performance profile can be modeled analytically. We then utilize multiple such transceivers in a communication system operating at millimeter-wave carrier frequencies. Various aspects of the system are analyzed, including the optimum achievable throughput for a given amount of total consumed power. An analogy is drawn between the “transceiver cell” proposed herein and a “computational cell” commonly used in neural networks that allows us to apply neural-network type algorithms to aid in difficult tasks such as channel estimation for a large number of transceivers.","PeriodicalId":305510,"journal":{"name":"2017 Information Theory and Applications Workshop (ITA)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Information Theory and Applications Workshop (ITA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITA.2017.8023454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
We analyze a one-bit wireless transceiver whose architecture is simple enough that its power versus performance profile can be modeled analytically. We then utilize multiple such transceivers in a communication system operating at millimeter-wave carrier frequencies. Various aspects of the system are analyzed, including the optimum achievable throughput for a given amount of total consumed power. An analogy is drawn between the “transceiver cell” proposed herein and a “computational cell” commonly used in neural networks that allows us to apply neural-network type algorithms to aid in difficult tasks such as channel estimation for a large number of transceivers.