Performance Analysis of Different Flexible Decoding Algorithms for NR-LDPC Codes Performance Analysis
Main Article Content
Abstract
Channel coding technique is a fundamental building block in any modern communication system to realize reliable, fast, and secure data transmission. At the same time, it is a challenging and crucial task, as the data transmission happens in a channel where noise, fading, and other impairments are present. The Low-Density Parity-Check (LDPC) codes give substantial results close to the Shannon limit when the complexity and processing delay time are unlimited. In this paper, the performance of the LDPC decoding with four algorithms was investigated. The investigated four algorithms were Belief Propagation (BP), Layered Belief Propagation (LBP), Normalized min-sum (NMS), and Offset min-sum (OMS). These algorithms were examined for code rates ranging from 1/3 to 9/10 and message block lengths (64, 512, 1024, and 5120) bits. The simulation results revealed the flexibility of these decoders in supporting these code rates and block lengths, which enables their usage in a wide range of applications and scenarios for fifth-generation (5G) wireless communication. In addition, the effect of the maximum number of decoding iterations on the error correction performance was investigated, and a gain of 5.6 dB can be obtained by using 32 decoding iterations at BER=2*10-3 instead of one decoding iteration. The results showed that the decoders performed better for longer message blocks than for short message blocks, and less power was required for transmitting longer messages. Finally, the comparison results of their performance in terms of bit error rate (BER) under the same conditions showed a gain of 0.8 dB using LBP at BER= 10-5 compared with the NMS decoding algorithm.
Metrics
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY LICENSE http://creativecommons.org/licenses/by/4.0/
Plaudit
References
Aljanabi A, Alluhaibi O, Ahmed QZ, Khan FA, Waqas-Bin-Abbas, Lazaridis P. Low complexity single carrier frequency domain detectors for internet of underwater things (IoUT)s. wireless personal communications 2022; 125: 2443–2461.
Li M, Yuan H, Li M, Maple C, Li Y, Alluhaibi O. Security outage probability analysis of cognitive networks with multiple eavesdroppers for industrial internet of things. IEEE Transactions on Cognitive Communications and Networking 2022; 8 (3):1422 - 1433.
Alabady SA, Al-Turjman F. Low complexity parity check code for futuristic wireless networks applications. IEEE Access 2018; 6:18398-18407.
Čarapić D, Maksimovi M, Forcan M. Performance analysis of LDPC and Polar codes for message transmissions over different channel models. 8th International Conference on Electronics, Telecommunications, Computing, Automatics and Nuclear Engineering - IcETRAN 2021 September 8-10; Ethno village Stanišići, Republic of Srpska: p.1–6.
Ji W, Wu Z, Zheng K, Zhao L, Liu Y. Design and implementation of a 5G NR system based on LDPC in open source SDR. IEEE Globecom Workshops (GC Wkshps) 2018 December 09-13; Abu Dhabi, United Arab Emirates: p.1–6.
Maksimovi M, Forcan M. Application of 5G channel coding techniques in smart grid : LDPC vs . Polar coding for command messaging. 7th International Conference on Electronics, Telecommunications, Computing, Automatics and Nuclear Engineering - IcETRAN 2020 June 8-10; Belgrade, Serbia: p.746–751.
Wu H, Wang H. Decoding latency of LDPC codes in 5G NR. 29th International Telecommunication Networks and Applications Conference (ITNAC) 2019 November 27-29, Auckland, New Zealand: p. 0–4.
Valenti MC, Sun J. Turbo codes. In: Farid Dowla, Handbook of Rf and Wireless Technologies. 1st ed., USA: Newnes; 2003.
Shannon CE. A Mathematical theory of communication. Bell System Technical Journal 1948; 27 (3): 379–423.
Indoonundon M, Fowdur TP. Overview of the challenges and solutions for 5G channel coding schemes. Journal of Information and Telecommunication 2021; 5 (4): 460–483.
Goldsmith A. Wireless communications. Cambridge, England: Cambridge university press; 2005.
Gallager R. Low-density parity-check codes. IRE Transactions on Information Theory 1962; 8 (1): 21–28.
MacKay DJC, Neal RM. Near Shannon limit performance of low density parity check codes. Electronics Letters 1996; 32 (18): 1645–1646.
MacKay DJC, Neal RM. Good codes based on very sparse matrices. 5th IMA International Conference on Cryptography and Coding 1995 December 18th-20th ; Cirencester, UK. Royal Agricultural College: p. 100–111.
Abusedra LF, Daeri AM, Zerek AR. Implementation and performance study of the LDPC coding in the DVB-S2 link system using MATLAB. ” 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA) 2016 December 19-21; Sousse, Tunisia: p. 669–674.
Nguyen TTB, Tan TN, Lee H. Low-complexity high-throughput qc-ldpc decoder for 5g new radio wireless communication. electronics 2021; 10 (4): 516.
Arikan E. Channel polarization: A method for constructing capacity-achieving codes for symmetric binary-input memoryless channels. IEEE Transactions on Information Theory 2009; 55 (7): 3051–3073.
Awais M, Condo C. Flexible LDPC decoder architectures. VLSI Design 2012, 2012.
Rao KD, Channel coding techniques for wireless communications. 2nd ed., India: Springer; 2015.
Hocevar DE. A reduced complexity decoder architecture via layered decoding of LDPC codes. IEEE Workshop on Signal Processing Systems 2004 SIPS 2004 October 13-15; Austin, TX, USA: p. 107–112.
International Telecommunication Union- Radiocommunication Sector M.2083. IMT Vision-Framework and overall objectives of the future development of IMT for 2020 and beyond. Electronic Publication : Geneva; 2015: pp.1-19.
European Telecommunications Standards Institude- Technical Specification # 138 212 - V15.2.0 - 5G; NR; Multiplexing and channel coding. Sophia Antipolis Cedex, France; 2018: pp. 1-101,
Proakis JG, Salehi M. Fundamentals of communication systems. 2nd ed., India :Pearson Education, 2007.
Tahir B, Schwarz S, Rupp M. BER comparison between Convolutional, Turbo, LDPC, and Polar codes. 24th international conference on telecommunications (ICT) 2017 May 3-5; Limassol, Cyprus: p. 1–7.
Nguyen TTB, Tan TN, Lee H. Efficient QC-LDPC encoder for 5G new radio. electronics 2019; 8 (6): 668.
Richardson TJ, Urbanke RL. Efficient encoding of low-density parity-check codes. IEEE Transactions on Information Theory 2001; 47 (2): 638–656.
Petrović VL, El Mezeni DM, Radošević A. Flexible 5g new radio ldpc encoder optimized for high hardware usage efficiency. electronics 2021; 10 (9): 1106.
Gallager RG. Low-Density Parity-Check Codes. Massachusetts Institute of Technology Cambridge, Massachusetts, USA;1963: pp.1-90.
Chen J, Tanner RM, Jones C, Li Y. Improved min-sum decoding algorithms for irregular LDPC codes. IEEE International Symposium on Information Theory, Proceedings 2005 September 04-09; Adelaide, SA, Australia. p.1-5.
Chen J, Fossorier MPC. Density evolution for two improved BP-based decoding algorithms of LDPC codes. IEEE Communications Letters 2002; 6 (5): 208–210.