{"title":"基于矢量量化的前传数据压缩方案","authors":"Chenwei Feng, Mingxia Lin, Xinlin Xie, Mingjiang Zhang","doi":"10.1145/3366194.3366238","DOIUrl":null,"url":null,"abstract":"With the rapid development of the mobile communication technology, the number of long-term evolution (LTE) users and the volume of data is continually increasing, which greatly increases the amount of data transferred by fronthaul, resulting in a huge investment in optical fiber resource. In order to control the consumption of optical fiber resource, lower the cost of operator and avoid congestion in the premise of increasing data volume, it is necessary to compress the data for fronthaul. According to the characteristics of the LTE baseband signal, this paper proposes a data compression scheme on the basis of discrete cosine transform (DCT) and vector quantization. Firstly, the time domain signal is transformed in DCT. And then, the k-means clustering algorithm is used for vector quantization on the transformed signal. Finally, the Huffman coding is applied to further increase the compression ratio (CR) under the promise of an acceptable error. The simulation results show that the scheme proposed has a good performance in both compression ratio and error vector Magnitude (EVM) for the LTE baseband signal base on orthogonal frequency division multiplexing (OFDM).","PeriodicalId":105852,"journal":{"name":"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Data Compression Scheme for Fronthaul Based on Vector Quantization\",\"authors\":\"Chenwei Feng, Mingxia Lin, Xinlin Xie, Mingjiang Zhang\",\"doi\":\"10.1145/3366194.3366238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of the mobile communication technology, the number of long-term evolution (LTE) users and the volume of data is continually increasing, which greatly increases the amount of data transferred by fronthaul, resulting in a huge investment in optical fiber resource. In order to control the consumption of optical fiber resource, lower the cost of operator and avoid congestion in the premise of increasing data volume, it is necessary to compress the data for fronthaul. According to the characteristics of the LTE baseband signal, this paper proposes a data compression scheme on the basis of discrete cosine transform (DCT) and vector quantization. Firstly, the time domain signal is transformed in DCT. And then, the k-means clustering algorithm is used for vector quantization on the transformed signal. Finally, the Huffman coding is applied to further increase the compression ratio (CR) under the promise of an acceptable error. The simulation results show that the scheme proposed has a good performance in both compression ratio and error vector Magnitude (EVM) for the LTE baseband signal base on orthogonal frequency division multiplexing (OFDM).\",\"PeriodicalId\":105852,\"journal\":{\"name\":\"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3366194.3366238\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3366194.3366238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data Compression Scheme for Fronthaul Based on Vector Quantization
With the rapid development of the mobile communication technology, the number of long-term evolution (LTE) users and the volume of data is continually increasing, which greatly increases the amount of data transferred by fronthaul, resulting in a huge investment in optical fiber resource. In order to control the consumption of optical fiber resource, lower the cost of operator and avoid congestion in the premise of increasing data volume, it is necessary to compress the data for fronthaul. According to the characteristics of the LTE baseband signal, this paper proposes a data compression scheme on the basis of discrete cosine transform (DCT) and vector quantization. Firstly, the time domain signal is transformed in DCT. And then, the k-means clustering algorithm is used for vector quantization on the transformed signal. Finally, the Huffman coding is applied to further increase the compression ratio (CR) under the promise of an acceptable error. The simulation results show that the scheme proposed has a good performance in both compression ratio and error vector Magnitude (EVM) for the LTE baseband signal base on orthogonal frequency division multiplexing (OFDM).