LDPC and Polar Codes in 6G: A Comparative Study and Unified Frameworks

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Abstract

Relevance. As sixth-generation (6G) wireless systems pursue extreme requirements in throughput, latency, reliability, and adaptability, the design of channel coding schemes becomes increasingly critical. This paper presents a comprehensive comparison between Low-Density Parity-Check (LDPC) codes and Polar codes, the two most promising channel coding candidates for 6G. We analyze their respective strengths across key metrics including data throughput, error-correction capability, decoding complexity, hardware implementation, and adaptability to dynamic communication scenarios. Furthermore, we explore recent advances in unified channel coding frameworks, including generalized LDPC with Polar-like components (GLDPC-PC) and artificial intelligence (AI)-assisted decoders, which aim to bridge the performance gap across diverse 6G scenarios. Purpose. This paper aims to provide a systematic and measurable comparison of LDPC and Polar codes for 6G, while also examining the feasibility of unified coding frameworks to bridge their performance gaps.Methods used. This study employs a systematic literature review. The analysis first evaluates LDPC and Polar codes against four key metrics: data throughput, error-correction capability, decoding complexity and hardware implementation, and flexibility. It then examines advancements in long- and short-block code design and unified frameworks. The comparison is substantiated by a quantitative analysis of documented performance data.Results. LDPC codes demonstrate strong hardware scalability and parallelism, while Polar codes excel in short-packet error correction. Unified approaches integrate their advantages, enhancing adaptability to diverse scenarios.Novelty. Unlike prior works with fragmented analyses, this study combines comparative evaluation with an exploration of unified frameworks, providing an integrated perspective.Theoretical significance. The results enrich theoretical understanding of 6G coding trade-offs. The paper offers a guidance for researchers and standardization bodies in designing future coding strategies.Practical significance. The practical significance of the work lies in the fact that the conducted comparative study of LDPC and Polar codes enables a well-founded selection of channel coding schemes for various 6G communication scenarios. The obtained results can be used in the design of 6G communication systems to optimize the choice between codes: Polar codes are suitable for short packets requiring low latency and high energy efficiency, while LDPC codes (particularly SC-LDPC) are ideal for long codes where hardware scalability and parallelism are critical. The results are also applicable to the development of unified decoders and adaptive systems capable of dynamically switching between schemes, which enhances the flexibility and efficiency of future telecommunication infrastructures.

About the authors

W. Zhang

Tomsk State University of Control Systems and Radioelectronics

Email: zhangweijia@ieee.org
ORCID iD: 0000-0003-2252-2750

T. R. Gazizov

Tomsk State University of Control Systems and Radioelectronics

Email: talgat.r.gazizov@tusur.ru
ORCID iD: 0000-0002-1192-4853

References

  1. Zhang H., Tong W. Channel Coding for 6G Extreme Connectivity – Requirements, Capabilities, and Fundamental Tradeoffs // IEEE BITS the Information Theory Magazine. 2023. Vol. 3. Iss. 1. PP. 54–66. doi: 10.1109/MBITS.2023.3322978
  2. Lu Y., Zheng X. 6G: A survey on technologies, scenarios, challenges, and the related issues // Journal of Industrial Information Integration. 2020. Vol. 19. Р. 100158. doi: 10.1016/j.jii.2020.100158. EDN:BIOOJV
  3. Zong B., Fan C., Wang X., Duan X., Wang B., Wang J. 6G Technologies: Key Drivers, Core Requirements, System Architectures, and Enabling Technologies // IEEE Vehicular Technology Magazine. 2019. Vol. 14. Iss. 3. PP. 18–27. doi: 10.1109/MVT. 2019.2921398
  4. Berrou C., Glavieux A., Thitimajshima P. Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1 // Proceedings of IEEE International Conference on Communications (ICC’93, Geneva, Switzerland, 23–26 May 1993). IEEE, 1993. Vol. 2. PP. 1064–1070. doi: 10.1109/ICC.1993.397441
  5. Yue C., Miloslavskaya V., Shirvanimoghaddam M., Vucetic B., Li Y. Efficient Decoders for Short Block Length Codes in 6G URLLC // IEEE Communications Magazine. 2023. Vol. 61. Iss. 4. PP. 84–90. doi: 10.1109/MCOM.001.2200275. EDN:PULBIK
  6. Rowshan M., Qiu M., Xie Y., Gu X., Yuan J. Channel Coding Toward 6G: Technical Overview and Outlook // IEEE Open Journal of the Communications Society. 2024. Vol. 5. PP. 2585–2685. doi: 10.1109/OJCOMS.2024.3390000. EDN:WBHYCS
  7. Miao S., Kestel C., Johannsen L., Geiselhart M., Schmalen L., Balatsoukas-Stimming A., et al. Trends in Channel Coding for 6G // Proceedings of the IEEE. 2024. Vol. 112. Iss. 7. PP. 653–675. doi: 10.1109/JPROC.2024.3416050
  8. Gautam A., Thakur P., Singh G. Advanced channel coding schemes for B5G/6G networks: State-of-the-art analysis, research challenges and future directions // International Journal of Communication Systems. 2024. Vol. 37. Iss. 13. P. e5855. doi: 10.1002/dac.5855. EDN:WMSPSO
  9. Gallager R. Low-density parity-check codes // IRE Transactions on Information Theory. 1962. Vol. 8. Iss. 1. PP. 21–28. doi: 10.1109/TIT.1962.1057683
  10. Chen L., Xu J., Djurdjevic I., Lin S. Near-Shannon-limit quasi-cyclic low-density parity-check codes // IEEE Transactions on Communications. 2004. Vol. 52. Iss. 7. PP. 1038–1042. doi: 10.1109/TCOMM.2004.831353
  11. Fossorier M.P. Quasicyclic low-density parity-check codes from circulant permutation matrices // IEEE Transactions on Information Theory. 2004. Vol. 50. Iss. 8. PP. 1788–1793. doi: 10.1109/TIT.2004.831841
  12. Li M., Derudder V., Bertrand K., Desset C., Bourdoux A. High-Speed LDPC Decoders Towards 1 Tb/s // IEEE Transactions on Circuits and Systems I: Regular Papers. 2021. Vol. 68. Iss. 5. PP. 2224–2233. doi: 10.1109/TCSI.2021.3060880. EDN:UTRSUU
  13. Tanner R. A recursive approach to low complexity codes // IEEE Transactions on Information Theory. 1981. Vol. 27. Iss. 5. PP. 533–547. doi: 10.1109/TIT.1981.1056404
  14. Zhu H., Pu L., Xu H., Zhang B. Construction of Quasi-Cyclic LDPC Codes Based on Fundamental Theorem of Arithmetic // Wireless Communications and Mobile Computing. 2018. P. 5264724. doi: 10.1155/2018/5264724
  15. Vatta F., Soranzo A., Babich F. Low-complexity bound on irregular LDPC belief-propagation decoding thresholds using a Gaussian approximation // Electronics Letters. 2018. Vol. 54. Iss. 17. PP. 1038–1040. doi: 10.1049/el.2018.0478
  16. MacKay D.J., Neal R.M. Near Shannon limit performance of low density parity check codes // Electronics Letters. 1997. Vol. 33. Iss. 6. PP. 457–458. doi: 10.1049/el:19961141
  17. Arikan E. Channel Polarization: A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels // IEEE Transactions on Information Theory. 2009. Vol. 55. Iss. 7. PP. 3051–3073. doi: 10.1109/TIT. 2009.2021379
  18. Tal I., Vardy A. List Decoding of Polar Codes // IEEE Transactions on Information Theory. 2015. Vol. 61. Iss. 5. PP. 2213–2226. doi: 10.1109/TIT.2015.2410251
  19. Niu K., Chen K. CRC-Aided Decoding of Polar Codes // IEEE Communications Letters. 2012. Vol. 16. Iss. 10. PP. 1668–1671. doi: 10.1109/LCOMM.2012.090312.121501
  20. Kestel C., Herrmann M., Wehn N. When Channel Coding Hits the Implementation Wall // Proceedings of the 2018 IEEE 10th International Symposium on Turbo Codes & Iterative Information Processing (ISTC, Hong Kong, China, 03–07 December 2018). IEEE, 2018. doi: 10.1109/ISTC.2018.8625324
  21. Sarkis G., Giard P., Vardy A., Thibeault C., Gross W.J. Fast Polar Decoders: Algorithm and Implementation // IEEE Journal on Selected Areas in Communications. 2014. Vol. 32. Iss. 5. PP. 946–957. doi: 10.1109/JSAC.2014.140514
  22. Giard P., Sarkis G., Thibeault C., Gross W.J. Multi-Mode Unrolled Architectures for Polar Decoders // IEEE Transactions on Circuits and Systems I: Regular Papers. 2016;63(9):1443–1453. doi: 10.1109/TCSI.2016.2586218
  23. Alamdar-Yazdi A., Kschischang F.R. A Simplified Successive-Cancellation Decoder for Polar Codes // IEEE Communications Letters. 2011. Vol. 15. Iss. 12. PP. 1378–1380. doi: 10.1109/LCOMM.2011.101811.111480
  24. Tong J., Wang X., Zhang Q., Zhang H., Wang J., Tong W. Fast polar codes for terabits-per-second throughput communications // Proceedings of the 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC, Toronto, Canada, 05‒08 September 2023). IEEE, 2023. doi: 10.1109/PIMRC56721.2023.10293973
  25. Ghanaatian R., Balatsoukas-Stimming A., Müller T.C., Meidlinger M., Matz G., Teman A., Burg A. A 588-Gb/s LDPC Decoder Based on Finite-Alphabet Message Passing // IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 2017. Vol. 26. Iss. 2. PP. 329–340. doi: 10.1109/TVLSI.2017.2766925
  26. Amirzade F., Sadeghi M-R., Panario D. QC-LDPC Codes With Large Column Weight and Free of Small Size ETSs // IEEE Communications Letters. 2021. Vol. 26. Iss. 3. PP. 500–504. doi: 10.1109/LCOMM.2021.3138936. EDN:GIEZGG
  27. Farsiabi A., Banihashemi A.H. Error Floor Analysis of LDPC Row Layered Decoders // IEEE Transactions on Information Theory. 2021. Vol. 67. Iss. 9. PP. 5804–5826. doi: 10.1109/TIT.2021.3099020. EDN:IWPNIO
  28. Liu X., Wu S., Wang Y., Zhang N., Jiao J., Zhang Q. Exploiting Error-Correction-CRC for Polar SCL Decoding: A Deep Learning-Based Approach // IEEE Transactions on Cognitive Communications and Networking. 2019. Vol. 6. Iss. 2. PP. 817–828. doi: 10.1109/TCCN.2019.2946358. EDN:LEXLBJ
  29. Liu Y., Olmos P.M., Mitchell D.G. Generalized LDPC Codes for Ultra Reliable Low Latency Communication in 5G and Beyond // IEEE Access. 2018. Vol. 6. PP. 72002–72014. doi: 10.1109/ACCESS.2018.2880997
  30. Wang T., Qu D., Jiang T. Parity-check-concatenated polar codes // IEEE Communications Letters. 2016. Vol. 20. Iss. 12. PP. 2342–2345. doi: 10.1109/ACCESS.2018.2880997. EDN:OYJJXQ
  31. Asif M., Khan W.U., Afzal H.R., Nebhen J., Ullah I., Rehman A.U., Kaabar M.K. Reduced-Complexity LDPC Decoding for Next-Generation IoT Networks // Wireless Communications and Mobile Computing. 2021. doi: 10.1155/2021/2029560. EDN:TRRDMB
  32. Niu K. Advanced Channel Coding for 6G // In: Lin X., Zhang J., Liu Y., Kim J. (eds.) Fundamentals of 6G Communications and Networking. Springer, 2023. PP. 259–290. doi: 10.1007/978-3-031-37920-8_10
  33. Herrmann M., Wehn N., Thalmaier M., Fehrenz M., Lehnigk-Emden T., Alles M. A 336 Gbit/s Full-Parallel Window Decoder for Spatially Coupled LDPC Codes // Proceedings of the Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit, Porto, Portugal, 08‒11 June 2021). IEEE, 2021. PP. 508–513. doi: 10.1109/EuCNC/6GSummit51104.2021.9482457
  34. Kam D., Kong B.Y., Lee Y. Low-Latency SCL Polar Decoder Architecture Using Overlapped Pruning Operations // IEEE Transactions on Circuits and Systems I: Regular Papers. 2023. Vol. 70. Iss. 3. PP. 1417–1427. doi: 10.1109/TCSI.2022.3230589. EDN:XPVRKY
  35. Tai Y., Li K., Zhou L., Liu S., Zhang X. An Improved CA-SCL Decoding Algorithm for Polar Code // Proceedings of the International Symposium on Networks, Computers and Communications (ISNCC, Shenzhen, China, 19‒22 July 2022). IEEE, 2022. doi: 10.1109/ISNCC55209.2022.9851768
  36. Kim B., Park I-C. Area-Efficient QC-LDPC Decoder Architecture Based on Stride Scheduling and Memory Bank Division // IEICE Transactions on Communications. 2013. Vol. E96. Iss. 7. PP. 1772–1779. doi: 10.1587/transcom.E96.B.1772
  37. Bezner P., Clausius J., Geiselhart M., Janz T., Krieg F., Obermüller S., et al. Towards Flexible LDPC Coding for 6G // Proceedings of the 58th Asilomar Conference on Signals, Systems, and Computers (Pacific Grove, USA, 27‒30 October 2024). IEEE, 2024. PP. 1119–1125. doi: 10.1109/IEEECONF60004.2024.10942769
  38. Bae J.H., Abotabl A., Lin H-P., Song K-B., Lee J. An overview of channel coding for 5G NR cellular communications // APSIPA Transactions on Signal and Information Processing. 2019. Vol. 8. Iss. 1. P. e17. doi: 10.1017/ATSIP.2019.10
  39. Alqudah A.A., Hayajneh K.F., Aldiabat H.A., Shakhatreh H.M. Efficient Generation of Puncturing-Assisted Rate-Matched 5G New Radio LDPC Codes for Faster-Than-Nyquist Signaling // Journal of Communications. 2024. Vol. 19. Iss. 2. PP. 90‒98 doi: 10.12720/jcm.19.2.90-98. EDN:UUKNAC
  40. Nguyen C.T., Le H.D., Nguyen C.T., Pham A.T. Toward Practical HARQ-Based RC-LDPC Design for Optical Satellite-Assisted Vehicular Networks // IEEE Transactions on Aerospace and Electronic Systems. 2024. Vol. 60. Iss. 6. PP. 8619‒8634 doi: 10.1109/TAES.2024.3434768
  41. Yuan R., Xie T., Jin Y. Dynamic Maximum Iteration Number Scheduling LDPC Decoder for Space-Based Internet of Things // Proceedings of the 5th EAI International Conference on IoT as a Service (IoTaaS 2019, Xi’an, China, 16–17 November 2019). Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Cham: Springer, 2020. Vol. 316. PP. 235–241. doi: 10.1007/978-3-030-44751-9_20
  42. Korada S.B., Şaşoğlu E., Urbanke R. Polar Codes: Characterization of Exponent, Bounds, and Constructions // IEEE Transactions on Information Theory. 2010. Vol. 56. Iss. 12. PP. 6253–6264. doi: 10.1109/TIT.2010.2080990
  43. Hassani S.H., Urbanke R. Universal polar codes // Proceedings of the 2014 IEEE International Symposium on Information Theory (ISIT, Honolulu, USA, 29 June ‒ 04 July 2014). IEEE, 2014. PP. 1451–1455. doi: 10.1109/ISIT.2014.6875073
  44. Sun S., Zhang Z. Designing Practical Polar Codes Using Simulation-Based Bit Selection // IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 2017. Vol. 7. Iss. 4. PP. 594–603. doi: 10.1109/JETCAS.2017.2759253. EDN:YEMWHJ
  45. Miloslavskaya V., Li Y., Vucetic B. Frozen Set Design for Precoded Polar Codes // IEEE Transactions on Communications. 2024. Vol. 73. Iss. 1. PP. 77–92. doi: 10.1109/TCOMM.2024.3439431
  46. Zhu H., Zhao Y. A Mapping Shortening Algorithm for Polar Codes // IEEE Access. 2019. Vol. 7. PP. 87110–87117. doi: 10.1109/ACCESS.2019.2926739. EDN:BLYVAC
  47. Zhu H., Guan P., Cao Z., Zhao Y. Rate-compatible systematic polar codes // IET Communications. 2021. Vol. 15. Iss. 15. PP. 1930–1940. doi: 10.1049/cmu2.12204. EDN:OTVRFX
  48. Trifonov P., Miloslavskaya V. Polar codes with dynamic frozen symbols and their decoding by directed search // Proceedings of the 2013 IEEE Information Theory Workshop (ITW, Seville, Spain, 09‒13 September 2013). IEEE, 2013. doi: 10.1109/ITW.2013.6691213. EDN:SLLYAP
  49. Miloslavskaya V., Li Y., Vucetic B. Design of Compactly Specified Polar Codes With Dynamic Frozen Bits Based on Reinforcement Learning // IEEE Transactions on Communications. 2023. Vol. 72. Iss. 3. PP. 1257–1272. doi: 10.1109/TCOMM.2023.3331532. EDN:LHWQVZ
  50. Coşkun M.C., Durisi G., Jerkovits T., Liva G., Ryan W., Stein B., et al. Efficient error-correcting codes in the short blocklength regime // Physical Communication. 2019. Vol. 34. PP: 66–79. doi: 10.1016/j.phycom.2019.03.004. EDN:XBHSNP
  51. Zhong X., Sham C-W., Ma S.L., Chou H-F., Mostaani A., Vu T.X., et al. Joint Source-Channel Coding System for 6G Communication: Design, Prototype and Future Directions // IEEE Access. 2024. Vol. 12. PP. 72034–72046. doi: 10.1109/ACCESS.2024.3360003. EDN:FJYGPJ
  52. Herrmann M., Wehn N. Beyond 100 Gbit/s Pipeline Decoders for Spatially Coupled LDPC Codes // EURASIP Journal on Wireless Communications and Networking. 2022. P. 90. doi: 10.1186/s13638-022-02169-5. EDN:JHMSIO
  53. Li H., Yu Z., Lu T., Zheng W., Feng H., Ma Z., et al. Novel memory efficient LDPC decoders for beyond 5G // Physical Communication. 2022. Vol. 51. P. 101538. doi: 10.1016/j.phycom.2021.101538. EDN:KGHOML
  54. Presman N., Litsyn S. Recursive Descriptions of Polar Codes // arXiv:1209.4818. 2012. doi: 10.48550/arXiv.1209.4818
  55. Rowshan M., Viterbo E. Stepped List Decoding for Polar Codes // Proceedings of the 10th International Symposium on Turbo Codes & Iterative Information Processing (ISTC, Hong Kong, China, 03‒07 December 2018). IEEE, 2018. doi: 10.1109/ISTC.2018.8625267
  56. Zhu K., Wu Z. Comprehensive Study on CC-LDPC, BC-LDPC and Polar Code // Proceedings of the 2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW, Seoul, South Korea, 06‒09 April 2020). IEEE, 2020. doi: 10.1109/WCNCW48565.2020.9124897. EDN:XOIQZR
  57. Wehn N., Sahin O., Herrmann M. Forward-Error-Correction for Beyond-5G Ultra-High Throughput Communications // Proceedings of the 11th International Symposium on Topics in Coding (ISTC, Montreal, Canada, 30 August ‒ 03 September 2021). IEEE, 2021. doi: 10.1109/ISTC49272.2021.9594126
  58. Ren Y., Zhang L., Shen Y., Song W., Boutillon E., Balatsoukas-Stimming A., et al. Edge-Spreading Raptor-Like LDPC Codes for 6G Wireless Systems // arXiv:2410.16875. 2024. doi: 10.48550/arXiv.2410.16875
  59. Ren Y., Shen Y., Song W., Balatsoukas-Stimming A., Boutillon E., Burg A. Towards 6G: Configurable High-Throughput Decoder Implementation for SC-LDPC Codes // Proceedings of the 58th Asilomar Conference on Signals, Systems, and Computers (Pacific Grove, USA, 27‒30 October 2024). IEEE, 2024. PP. 980–984. doi: 10.1109/IEEECONF60004.2024.10942947
  60. Hashemi S.A., Condo C., Gross W.J. Fast and Flexible Successive-Cancellation List Decoders for Polar Codes // IEEE Transactions on Signal Processing. 2017. Vol. 65. Iss. 21. PP. 5756–5769. doi: 10.1109/TSP.2017.2740204
  61. Wang C-X., You X., Gao X., Zhu X., Li Z., Zhang C., et al. On the Road to 6G: Visions, Requirements, Key Technologies, and Testbeds // IEEE Communications Surveys & Tutorials. 2023. Vol. 25. Iss. 2. PP. 905–974. doi: 10.1109/COMST.2023.3249835. EDN:WXUFKU
  62. Akbar M.S., Hussain Z., Ikram M., Sheng Q.Z., Mukhopadhyay S. On challenges of sixth-generation (6G) wireless networks: A comprehensive survey of requirements, applications, and security issues // Journal of Network and Computer Applications. 2024. Vol. 236. P. 104040. doi: 10.1016/j.jnca.2024.104040. EDN:OWJCFS
  63. Matsumine T., Ochiai H. Recent Advances in Deep Learning for Channel Coding: A Survey // IEEE Open Journal of the Communications Society. 2024. Vol. 5. PP. 2666–2693. doi: 10.1109/ojcoms.2024.3472094. EDN:TZENCY
  64. Geiselhart M., Krieg F., Clausius J., Tandler D., ten Brink S. 6G: A Welcome Chance to Unify Channel Coding? // IEEE BITS the Information Theory Magazine. 2023. Vol. 3. Iss. 1. PP. 67–80. doi: 10.1109/MBITS.2023.3322974
  65. Yan Y., Zhu J., Zheng T., He J., Jiang C., He J., et al. Error Correction Code Transformer: From Non-Unified to Unified // arXiv:2410.03364. 2024. doi: 10.48550/arXiv.2410.03364
  66. Shen L., Wu Y., Xu Y., You X., Gao X., Zhang W. GLDPC-PC Codes: Channel Coding Toward 6G Communications // IEEE Communications Magazine. 2025. Vol. 63. Iss. 10. PP. 165–171. doi: 10.1109/MCOM.005.2400259
  67. Qiao W., Liu D., Liu S. QFEC ASIP: A Flexible Quad-Mode FEC ASIP for Polar, LDPC, Turbo, and Convolutional Code Decoding // IEEE Access. 2018. Vol. 6. PP. 72189–72200. doi: 10.1109/ACCESS.2018.2883292
  68. Yue Y., Choi S., Ajayi T., Wei X., Dreslinski R., Blaauw D., et al. A Fully Configurable Unified FEC Decoder for LDPC, Polar, Turbo, and Convolutional Codes with Row-First Collision-Free Compression // Authorea Preprints. 2024. doi: 10.36227/techrxiv.171262833.36139863/v1

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