Author:
Feng Chenwei,Sun Yu,Su Youmei,Jiang Fuchun,Tao Lin,Ji Huazhi
Abstract
Abstract
With the rapid increase of global data traffic, storage and transmission of massive data is a challenging problem. Therefore, data compression is necessary. Based on DRoF, mobile fronthual has the advantages of high data rate, good connectivity and system capacity, and becomes the key part of communication system transmission. In this paper, an optimized vector quantization data compression algorithm based on DRoF system is proposed, which mainly studies OFDM baseband modulation signals. Firstly, the modulation signal is transformed by DCT. Then the optimized fast-global K-means clustering algorithm is used for quantization to overcome the problem that the original algorithm may choose noise points as the cluster center. Finally, Huffman coding is used to reduce the code length of the quantized data. Simulation results show that the proposed algorithm has good CR and EVM performance within the error tolerance range. It has a high degree of compression and signal recovery.
Subject
General Physics and Astronomy
Reference11 articles.
1. Overview of K-means algorithm for big data;Ren;Computer Application research,2020
2. DRoF technology for millimeter wave wireless access network;Ye;Journal of Internet of Things,2019
3. Load adaptive technology of fronthaul link in cloud mobile access network;Li;Journal of Liaocheng University (Natural Science Edition),2019
4. Digital mobile fronthaul employing differential pulse code modulation with suppressed quantization noise;Zhang;Optics Express,2017