Research Article
Analog Images Communication Based on Block Compressive Sensing
@INPROCEEDINGS{10.1007/978-3-030-41117-6_4, author={Min Wang and Bin Tan and Jiamei Luo and Qin Zou}, title={Analog Images Communication Based on Block Compressive Sensing}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part II}, proceedings_a={CHINACOM PART 2}, year={2020}, month={2}, keywords={Analog images communication Block compressive sensing Wireless image multicast}, doi={10.1007/978-3-030-41117-6_4} }- Min Wang
Bin Tan
Jiamei Luo
Qin Zou
Year: 2020
Analog Images Communication Based on Block Compressive Sensing
CHINACOM PART 2
Springer
DOI: 10.1007/978-3-030-41117-6_4
Abstract
Recently, owing to graceful performance degradation for various wireless channels, analog visual transmission has attracted considerable attention. The pioneering work about analog visual communication is SoftCast, and many advanced works are all based on the framework of SoftCast. In this paper, we propose a novel analog image communication system called CSCast based block compressive sensing. Firstly, we present the system framework and detailed design of CSCast, which consists of discrete wavelet transform, power scaling, compressive sampling and analog modulation. Furthermore, we discuss how to determine the appropriate value of scaling factor(\alpha )in power allocation, and block size of measurement matrix in compressive sampling. Simulations show that the performance of CSCast better than Softcast in all SNR range, and better than Cactus in high SRN range. In particular, CSCast outperforms over Softcast about 1.72 dB. And CSCast achieves the maximum average PSNR gain 1.8 dB over Cacuts and 2.03 dB over SoftCast when SNR = 25 dB, respectively. In addition, our analyses shows CSCast can save about 75% overhead comparing to SoftCast and Cactus.
