{"title":"现代无线通信系统中改进SL0算法的发展","authors":"Umesh Mahind, M. Kadam","doi":"10.1109/ICMETE.2016.120","DOIUrl":null,"url":null,"abstract":"In modern communication system, for compressive sensing, signal reconstruction involves searching a sparse solution. Till now several approaches to same problem have been measured in existing reconstruction algorithms. They provide a compromise between restoration capabilities and required computational time. In an effort to push the limits for this compromise, we consider a smoothed l0 norm (SL0) algorithm in a noiseless setup. In this paper, we proposed modified version of SL0 algorithm for modern wireless communication system. We argue that using a set of meticulously chosen parameters in our proposed modified SL0 algorithm may result in considerably good restoration capabilities in terms of phase transition while required less computational time as existing SL0 algorithms. A large set of simulations further support this claim. Simulation results show that, comparing with SL0 algorithm, the proposed method can exploit the sparse property with good performance.","PeriodicalId":167368,"journal":{"name":"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)","volume":"28 10","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of Modified SL0 Algorithm for Modern Wireless Communication System\",\"authors\":\"Umesh Mahind, M. Kadam\",\"doi\":\"10.1109/ICMETE.2016.120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In modern communication system, for compressive sensing, signal reconstruction involves searching a sparse solution. Till now several approaches to same problem have been measured in existing reconstruction algorithms. They provide a compromise between restoration capabilities and required computational time. In an effort to push the limits for this compromise, we consider a smoothed l0 norm (SL0) algorithm in a noiseless setup. In this paper, we proposed modified version of SL0 algorithm for modern wireless communication system. We argue that using a set of meticulously chosen parameters in our proposed modified SL0 algorithm may result in considerably good restoration capabilities in terms of phase transition while required less computational time as existing SL0 algorithms. A large set of simulations further support this claim. Simulation results show that, comparing with SL0 algorithm, the proposed method can exploit the sparse property with good performance.\",\"PeriodicalId\":167368,\"journal\":{\"name\":\"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)\",\"volume\":\"28 10\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMETE.2016.120\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMETE.2016.120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of Modified SL0 Algorithm for Modern Wireless Communication System
In modern communication system, for compressive sensing, signal reconstruction involves searching a sparse solution. Till now several approaches to same problem have been measured in existing reconstruction algorithms. They provide a compromise between restoration capabilities and required computational time. In an effort to push the limits for this compromise, we consider a smoothed l0 norm (SL0) algorithm in a noiseless setup. In this paper, we proposed modified version of SL0 algorithm for modern wireless communication system. We argue that using a set of meticulously chosen parameters in our proposed modified SL0 algorithm may result in considerably good restoration capabilities in terms of phase transition while required less computational time as existing SL0 algorithms. A large set of simulations further support this claim. Simulation results show that, comparing with SL0 algorithm, the proposed method can exploit the sparse property with good performance.