{"title":"Removal of the Feedback Loop in CCSDS 123.0-B-2 During Hardware Implementation","authors":"Liang Jia;Qi Wang;Lei Zhang;Chengpeng Song;Peng Zhang","doi":"10.1109/LGRS.2025.3601194","DOIUrl":null,"url":null,"abstract":"The Consultative Committee for Space Data Systems (CCSDS) proposed the CCSDS 123.0-B-2 standard for compressing large volumes of data acquired by multispectral and hyperspectral sensors. However, data dependencies in the CCSDS 123.0-B-2 predictor lead to feedback loops during the weight update process. This poses challenges for fully pipelined hardware implementation of the predictor and severely limits the achievable data throughput. Therefore, it is critical to improve throughput while keeping the degradation in compression performance within an acceptable range. This work demonstrates that by appropriately reducing the frequency of weight updates, the data dependencies in the predictor can be mitigated, thus shortening the critical path in hardware implementation and eliminating feedback loops. Experimental results show that under the band interleaved by line (BIL) data format, the proposed method achieves a throughput of 348.4 MSamples/s using only 3995 look-up tables (LUTs).","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4000,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11133588/","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
The Consultative Committee for Space Data Systems (CCSDS) proposed the CCSDS 123.0-B-2 standard for compressing large volumes of data acquired by multispectral and hyperspectral sensors. However, data dependencies in the CCSDS 123.0-B-2 predictor lead to feedback loops during the weight update process. This poses challenges for fully pipelined hardware implementation of the predictor and severely limits the achievable data throughput. Therefore, it is critical to improve throughput while keeping the degradation in compression performance within an acceptable range. This work demonstrates that by appropriately reducing the frequency of weight updates, the data dependencies in the predictor can be mitigated, thus shortening the critical path in hardware implementation and eliminating feedback loops. Experimental results show that under the band interleaved by line (BIL) data format, the proposed method achieves a throughput of 348.4 MSamples/s using only 3995 look-up tables (LUTs).