Stream-Based Lossless Compression of Sensor Signals Using an Integer Adaptive Predictor

Abstract

Real-time sensor signal acquisition poses new challenges in data transmission and storage. Therefore, it is beneficial to insert a lossless compression system between the sensor signal’s generation and subsequent data transmission. Additionally, the compression algorithm must consider both the compression ratio and throughput. This brief proposes a two-stage lossless compression system using an integer adaptive predictor to address the inherent data diversity in digital signals and improve the compression ratio. Meanwhile, high-throughput hardware architecture is implemented for the compression system. The experimental results show that our stream-based lossless compression system improves the compression ratio by 10.5%-40.0% compared with the traditional compressor; up to 16.9% compared with the reported stream-based compressor and can operate at a speed of 800MB/s on a field-programmable gate array (FPGA).