Estudo da Viabilidade da Compressão de Dados em Rádios Definidos por Software
Abstract
Software-defined radios — or SDR — bring a series of benefits such as fast prototyping of new wireless communication techniques. One of the open questions in using these devices is how to facilitate the transfer, processing, and storage of samples provided by an SDR. This paper aims to study the feasibility of implementing a lossless data compression algorithm in the internal FPGA (Field Programmable Gate Array)commonly found on SDR in order to increase the sample throughput between the radio and the host processor, as well as reducing the storage space. The results show that it is possible to obtain an average compression ratio of 1.55 times, considering the limited capacity of existing SDR to compute such algorithms.
Keywords:
Rádios Definidos por Software, Algoritmos de compressão sem perdas, Field Programmable Gate Array
References
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Breslau, L., Estrin, D., Yu, H., Fall, K., Floyd, S., Heidemann, J., Helmy, A., Huang, P., McCamne, S., Varadhan, K., et al. (2000). Advances in network simulation. Computer,33(5):59-67.
Cui, W. (2007). New LZW data compression algorithm and its FPGA implementation. In Proc. 26th Picture Coding Symposium (PCS 2007).
Dandalis, A. and Prasanna, V. K. (2005). Configuration compression for FPGA-based em-bedded systems. IEEE Transactions on Very Large Scale Integration (VLSI) Systems,13(12):1394-1398.
Dascal, V., Dolea, P., Cristea, O., and Palade, T. (2013). Low-cost SDR-based ground receiving station for LEO satellite operations. In 2013 1]th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TEL-SIKS), volume 02, pages 627-630.
Dillinger, M., Madani, K., and Alonistioti, N. (2005). Software defined radio: Architectures, systems and functions. John Wiley & Sons.
Ettus Research (2019). Especificações do modelo N200. Disponível emnttps://www.ettus.com/content/files/07495. Ettus N200-210DS Flyer HR. pdf (acessado em 01/12/2019).
Fowers, J., Kim, J.-Y., Burger, D., and Hauck, S. (2015). A scalable high-bandwidth architecture for lossless compression on fpgas. In 2015 IEEE 23rd Annual International Symposium on Field-Programmable Custom Computing Machines, pages 52-59.IEEE.
GNU Radio (2019). Página oficial do projeto GNU Radio. Disponível em http://gnuradio.org/ (acessado em 01/12/2019).
Huffman, D. A. (1952). A method for the construction of minimum-redundancy codes. Proceedings of the IRE, 40(9):1098-1101.
IEEE LAN/MAN Standards Committee (2013). 802.1 1ac-2013 TEEE standard for information technology - LAN/MAN - specific requirements - part 11: Wireless LANmedium access control (MAC) and physical layer (PHY) specification - amendment4: Enhancements for very high throughput for operation in bands below 6 GHz.
Linux Wireless (2015). About mac80211. Disponível em https://wireless.wiki.kernel.org/en/developers/documentation/mac80211 (acessado em 27/12/2019).
McHenry, M. A., Tenhula, P. A., McCloskey, D., Roberson, D. A., and Hood, C. S. (2006).Chicago spectrum occupancy measurements & analysis and a long-term studies proposal. In Proceedings of the first international workshop on Technology and policy foraccessing spectrum, page 1. ACM.
Mitola HI, J. and Maguire Jr, G. Q. (1999). Cognitive radio: making software radios more personal. IEEE Personal Communications, 6(4):13-18.
Qiao, W., Du, J., Fang, Z., Lo, M., Chang, M. F., and Cong, J. (2018). High-throughput lossless compression on tightly coupled CPU-FPGA platforms. In 2018 IEEE 26th Annual International Symposium on Field-Programmable Custom Computing Machines(FCCM), pages 37-44.
Reis, A. L. G., Barros, A. F., Lenzi, K. G., Meloni, L. G. P., and Barbin, S. E. (2012). Introduction to the software-defined radio approach. IEEE Latin America Transactions,10(1):1156-1161.
Rigler, S., Bishop, W., and Kennings, A. (2007). FPGA-based lossless data compression using huffman and LZ77 algorithms. In 2007 Canadian Conference on Electrical and Computer Engineering, pages 1235-1238.
Rondeau, T. W., Le, B., Rieser, C. J., and Bostian, C. W. (2004). Cognitive radios with genetic algorithms: Intelligent control of software defined radios. In Software defined radio forum technical conference, pages C3-C8.
Sayood, K. (2002). Lossless compression handbook. Elsevier.
Sayood, K. (2012). Introduction to Data Compression, Fourth Edition. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 4th edition.
Shannon, C. E. (1949). Communication in the presence of noise. Proceedings of the IRE,37(1):10-21.VANU (2019). SDR: Software defined radio. Disponível em http://www.vanu.com/documents/media/SoftwareDefinedRadio. pdf (acessado em 01/12/2019).
WARP Project (2019). Wireless open access research platform. Disponível em http://warpproject.org/trac/ (acessado em 01/12/2019).
Welch, T. A. (1984). A technique for high-performance data compression. Computer,17(6):8-19.
Wi-Fi Alliance (2019). Página oficial da Wi-Fi Alliance. Disponível em http://www.wi-fi.org/ (acessado em 01/12/2019).
Zhou, X., Ito, Y., and Nakano, K. (2016). An efficient implementation of Izw compressionin the fpga. In Carretero, J., Garcia-Blas, J., Ko, R. K., Mueller, P., and Nakano, K.,editors, Algorithms and Architectures for Parallel Processing, pages 512-520, Cham. Springer International Publishing.
Published
2020-12-07
How to Cite
DAYRELL, Paulo R. R.; PASSOS, Diego G.; PASSOS, Fernanda G. O..
Estudo da Viabilidade da Compressão de Dados em Rádios Definidos por Software. In: WORKSHOP ON MANAGEMENT AND OPERATION OF NETWORKS AND SERVICE (WGRS), 25. , 2020, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 249-262.
ISSN 2595-2722.
DOI: https://doi.org/10.5753/wgrs.2020.12465.
