Data Compression Scheme Based on Discrete Sine Transform and Lloyd-Max Quantization
| Title | Data Compression Scheme Based on Discrete Sine Transform and Lloyd-Max Quantization |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Feng, Chenwei, Wang, Xianling, Zhang, Zewang |
| Conference Name | Proceedings of the 3rd International Conference on Intelligent Information Processing |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-6496-6 |
| Keywords | Common Public Radio Interface, composability, compressive sampling, Cyber physical system, cyber physical systems, data compression, Discrete Sine Transform, Lloyd-Max, privacy, pubcrawl, resilience, Resiliency |
| Abstract | With the increase of mobile equipment and transmission data, Common Public Radio Interface (CPRI) between Building Base band Unit (BBU) and Remote Radio Unit (RRU) suffers amounts of increasing transmission data. It is essential to compress the data in CPRI if more data should be transferred without congestion under the premise of restriction of fiber consumption. A data compression scheme based on Discrete Sine Transform (DST) and Lloyd-Max quantization is proposed in distributed Base Station (BS) architecture. The time-domain samples are transformed by DST according to the characteristics of Orthogonal Frequency Division Multiplexing (OFDM) baseband signals, and then the coefficients after transformation are quantified by the Lloyd-Max quantizer. The simulation results show that the proposed scheme can work at various Compression Ratios (CRs) while the values of Error Vector Magnitude (EVM) are better than the limits in 3GPP. |
| URL | https://dl.acm.org/citation.cfm?doid=3232116.3232124 |
| DOI | 10.1145/3232116.3232124 |
| Citation Key | feng_data_2018 |