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FPGA Implementation of Scaled “Quasi-Cyclic LDPC” Decoder Using High-Level Synthesis

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Proceedings of First International Conference on Mathematical Modeling and Computational Science

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1292))

Abstract

The increased demands for quality, like high throughput, low-latency, wide coverage, energy consumption, cost and reliable connections in mobile services, multimedia, and data transmission impose the use of advance technical requirements for the next fifth-generation (5G) new radio (NR). One of the most crucial parts in the physical layer of the new generation is the error correction coding technique. Three schemes, namely “Turbo codes”, “low-density parity check (LDPC)”, and “polar codes” are potentially considered as the candidate codes for both data and control channels. The competition is evaluated in terms of error correction capability, computational complexity, and flexibility. The parallelism, flexibility, and high processing speed of “field-programmable gate array (FPGA)” make it preferable in prototyping and implementation of different codes. In this paper, design, implementation, experimental verification, and validation of the quasi-cyclic LDPC encoder and decoder are proposed on the AWGN channel using Kintex-7 FPGA. Codewords are constructed and simulated for different length and rates. The performance and architectural complexity in terms of the throughput and silicon area are presented based on Vivado high-level synthesis (HLS). The paper also studies the effect of applying scaling factors to alleviate the overestimation of the “extrinsic information” that exchanges during the iterative decoding process.

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References

  1. Gallager, R. G. (1963). Low Density Parity-Check Codes. Cambridge, MA: MIT Press.

    Book  Google Scholar 

  2. MacKay, D., & Neal, R. (1995, October) Good codes based on very sparse matrices. In: Proceedings of 5th IMA Conference Cryptography and Coding (pp. 100–111).

    Google Scholar 

  3. IEEE 802.11n. (2006). Wireless LAN Medium Access Control and Physical Layer Specifications: Enhancement for Higher Throughput, IEEE P802.11n/D1.0.

    Google Scholar 

  4. IEEE 802.16e. (2005). Air Interface for Fixed and Mobile Broad- band Wireless Access Systems, IEEE P802.16e/D12 Draft.

    Google Scholar 

  5. European Telecommunications Standards Institute (ET-SI). (2005). Digital Video Broadcasting (DVB) Second Generation Framing Structure for Broadband Satellite Applications, EN 302 307 v1.1.1.

    Google Scholar 

  6. CCSDS. (2011). CCSDS 131.0-B-2 Recommendation for Space Data System Standards; TM Synchronization and Channel Coding.

    Google Scholar 

  7. Oksman, V., & Galli, S. (2009). G.hn: The new ITU-T home networking standard. IEEE Communications Magazine, 47(10), 138–145.

    Article  Google Scholar 

  8. Hailes, P., Xu, L., Maunder, R. G., Al-Hashimi, B. M., & Hanzo, L. (2016). A survey of FPGA-based LDPC decoders. IEEE Communications Surveys and Tutorials, 18(2), 1098–1122.

    Google Scholar 

  9. Cai, Y., Jeon, S., Mai, K., & Kumar, B. V. K. V. (2009). Highly parallel FPGA emulation for LDPC error floor characterization in perpendicular magnetic recording channel. IEEE Transactions on Magnetics, 45(10), 3761–3764.

    Article  Google Scholar 

  10. Fossorier, M. P. C. (2004). Quasi-cyclic low-density parity-check codes from circulant permutation matrices. IEEE Transaction on Information Theory, 50(8), 1788–1793.

    Article  MathSciNet  Google Scholar 

  11. Wiberg, N. (1996). Codes and Decoding on General Graphs. Ph.D. thesis, Likoping University, Sweden.

    Google Scholar 

  12. Fossorier, M. P. C., Mihaljevic, M., & Lmai, H. (1999, May). Reduced complexity iterative decoding of low-density parity check codes based on belief propagation. IEEE Transactions on Communications, 47(5), 673–680.

    Google Scholar 

  13. Tanner, R. (1981). A recursive approach to low complexity codes. IEEE Transactions on Information Theory, 27(5), 533–547.

    Article  MathSciNet  Google Scholar 

  14. Chen, J., & Fossorier, M. (2002). Near optimum universal belief propagation based decoding of low-density parity check codes. IEEE Transactions on Communications, 50(3), 406–414.

    Article  Google Scholar 

  15. Chen, J., & Fossorier, M. (2002). Density evolution for two improved bp-based decoding algorithms of LDPC codes. IEEE Communications Letters, 6(5), 208–210.

    Article  Google Scholar 

  16. Chandrasetty, V. A., & Aziz, S. M. (2012). An area efficient LDPC decoder using a reduced complexity min-sum algorithm. Integrated VLSI Journal, 45(2), 141–148.

    Article  Google Scholar 

  17. Chandrasetty, V. A., & Aziz, S. M. (2010). FPGA implementation of high performance LDPC decoder using modified 2-bit min-sum algorithm. In: Proceedings of the 2nd International Conference on Computer Research and Development (pp. 881–885).

    Google Scholar 

  18. Shafiullah, D., Islam, M., Faisal, M., & Rahman, I. Optimized min-sum decoding algorithm for low density pc codes. In: 2012 14th International Conference on Advanced Communication Technology (ICACT) (pp. 475–480).

    Google Scholar 

  19. Xu, M., Wu, J., Zhang, M. (2010). A modified offset min-sum decoding algorithm for LDPC codes. In: 2010 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT) (pp. 19–22).

    Google Scholar 

  20. Hamad, A. A. (2013). Estimation of Two-Dimensional Correction Factors for Min-Sum Decoding of Regular LDPC Code. Scientific Research Magazine, Wireless Engineering and Technology, 4(4), 181–187. https://doi.org/10.4236/wet.2013.44027.

    Article  Google Scholar 

  21. Shimizu, K., Ishikawa, T., Togawa, N., Ikenaga, T., & Goto, S. (2005, October 2–5). Partially-parallel LDPC decoder based on high efficiency message-passing algorithm. In: Proceedings of the IEEE International Conference on Computer Design: VLSI in Computers and Processors (pp. 503–510).

    Google Scholar 

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Correspondence to Sarah Alaa Tamkeen .

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Tamkeen, S.A., Hamad, A.A. (2021). FPGA Implementation of Scaled “Quasi-Cyclic LDPC” Decoder Using High-Level Synthesis. In: Peng, SL., Hao, RX., Pal, S. (eds) Proceedings of First International Conference on Mathematical Modeling and Computational Science. Advances in Intelligent Systems and Computing, vol 1292. Springer, Singapore. https://doi.org/10.1007/978-981-33-4389-4_14

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