{"title":"基于子空间和矩阵的误差控制方法的比较研究","authors":"M. Brahimi, Fatiha Merazka","doi":"10.1109/ICAEE53772.2022.9962067","DOIUrl":null,"url":null,"abstract":"Subspace codes are codes in which codewords are subspaces from a given vector space over a finite field $\\mathbb{F}_{q}$. Their use for error correction in Random Linear Network Coding (RLNC)-based networks has been first proposed by Kötter and Kschischang. The rationale of their application in RLNC stems from the fact that information in RLNC is basically a vector space and as long as its basis is preserved, information will not be lost. Those codes share a set of similarities with rank metric codes, which are codes with codewords being $m \\times n$ matrices from the space $\\mathbb{F}_{q}^{m \\times n}$. In this paper, we compare the two codes and we provide insights and guidelines to follow when choosing between them for error correction. Particularly, we show that when a choice is possible for a given application, it will always be a tradeoff between code cardinality and correction capability.","PeriodicalId":206584,"journal":{"name":"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Comparative Study Between Subspace and Matrix-Based Error Control Solutions\",\"authors\":\"M. Brahimi, Fatiha Merazka\",\"doi\":\"10.1109/ICAEE53772.2022.9962067\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Subspace codes are codes in which codewords are subspaces from a given vector space over a finite field $\\\\mathbb{F}_{q}$. Their use for error correction in Random Linear Network Coding (RLNC)-based networks has been first proposed by Kötter and Kschischang. The rationale of their application in RLNC stems from the fact that information in RLNC is basically a vector space and as long as its basis is preserved, information will not be lost. Those codes share a set of similarities with rank metric codes, which are codes with codewords being $m \\\\times n$ matrices from the space $\\\\mathbb{F}_{q}^{m \\\\times n}$. In this paper, we compare the two codes and we provide insights and guidelines to follow when choosing between them for error correction. Particularly, we show that when a choice is possible for a given application, it will always be a tradeoff between code cardinality and correction capability.\",\"PeriodicalId\":206584,\"journal\":{\"name\":\"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAEE53772.2022.9962067\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAEE53772.2022.9962067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Comparative Study Between Subspace and Matrix-Based Error Control Solutions
Subspace codes are codes in which codewords are subspaces from a given vector space over a finite field $\mathbb{F}_{q}$. Their use for error correction in Random Linear Network Coding (RLNC)-based networks has been first proposed by Kötter and Kschischang. The rationale of their application in RLNC stems from the fact that information in RLNC is basically a vector space and as long as its basis is preserved, information will not be lost. Those codes share a set of similarities with rank metric codes, which are codes with codewords being $m \times n$ matrices from the space $\mathbb{F}_{q}^{m \times n}$. In this paper, we compare the two codes and we provide insights and guidelines to follow when choosing between them for error correction. Particularly, we show that when a choice is possible for a given application, it will always be a tradeoff between code cardinality and correction capability.