International Journal of Engineering and Modern Technology (IJEMT )
E-ISSN 2504-8848
P-ISSN 2695-2149
VOL. 11 NO. 3 2025
DOI: 10.56201/ijemt.vol.11.no3.
Efiyeseimokumo S Ikeremo and Ayibapreye K Benjamin
In need to offer multiple services, wireless mobile communication demands a huge amount of data capacity. Peak throughput, low latency, and substantial speed are delivered by 5G networks. Wireless communications increasingly depend on channel coding. Channel coding for the 5G communication networks is facing a fresh difficulty and Sum product algorithm (SPA) is the significant breakthrough in this area. This research evaluates performance of LDPC of Sum product algorithm (SPA) and LDPC of Min-Sum algorithm (MSA) as in channel coding contenders for the 5G communication networks for different coding rates of ½ and 2/3 and at the same block length of 1024. The simulations are implemented using MATLAB R2018b. As the quality criterion of a channel code, FER and BER of the coding schemes is displayed versus SNR for the same block lengths (L=1024) and different code rates of 1/2 and 2/3 correspondingly. The evaluations and comparisons are conducted in terms of FER and BER for the same block length (L=1024) and differing code rates of 1/2 and 2/3. It is evident from the results that the SPA surpasses the other rival algorithm for nearly in all code rates. Also, there is no error floor in case of SPA. Therefore, choice for faster algorithm which are sought for the 5G communication networks because its characteristic of Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC). Although SPA has demonstrated their potential, faster decoding performance enhancement for tiny block lengths is still an unresolved subject. Channel coding for 5G is a dynamic investigation area as to tackle various outstanding tasks in future.
Ldpc, Spa, Msa, 5g, Communication networks
Chung, S. Y., Forney, G. D., Richardson, T. J., & Urbanke, R. (2001). On the design of low-
density parity-check codes within 0.0045 dB of the Shannon limit. IEEE
Communications letters, 5(2), 58-60.
Dhanorkar, P., & Kalbande, M. (2017). Design of LDPC decoder using message passing
algorithm. In 2017 International Conference on Communication and Signal Processing
(ICCSP) (pp. 1923-1926). IEEE.
Emad Yousif, A., H Al-Jammas, M., & S Abdulaziz, A. (2024). MIMO Channel Coding:
Survey. International Journal of Computing and Digital Systems, 15(1), 1-8.
Gallager, R. (1962). Low-density parity-check codes. IRE Transactions on information
theory, 8(1), 21-28.
Gallager, R. G. (1968). Information theory and reliable communication (Vol. 588). New York:
Wiley.
Hamming, R. W. (1950). Error detecting and error correcting codes. The Bell system technical
journal, 29(2), 147-160.
Huo, X., Tian, S., Yang, Y., Yu, L., Zhang, W., & Li, A. (2024). SPA: Self-Peripheral-Attention
for
central–peripheral
interactions
in
endoscopic
image
classification
and
segmentation. Expert Systems with Applications, 245, 123053.
Hussami, N., Korada, S. B., & Urbanke, R. (2009). Performance of polar codes for channel and
source coding. In 2009 IEEE International Symposium on Information Theory (pp. 1488-
1492). IEEE.
Kumar, N., Kedia, D., & Purohit, G. (2023). A review of channel coding schemes in the 5G
standard. Telecommunication Systems, 1-26.
Kumar, A., Gaur, N., Chakravarthy, S., & Nanthaamornphong, A. (2024). Performance
Evaluation of 5G New Radio Physical Uplink Channels with LDPC and Polar Coding on
AWGN Channels. International Journal of Intelligent Systems and Applications in
Engineering, 12(16s), 698-701.
Kim, S., Sobelman, G.E., Lee, H. (2008). Adaptive quantization in min-sum based irregular
LDPC decoder. In IEEE International Symposium on Circuits and Systems (ISCAS),
Seattle, WA, pp. 536-539. https://doi.org/10.1109/ISCAS.2008.4541473
Liu, X., Huang, J. J., Zhao, W., Wang, Z., Chen, Z., & Pan, Y. (2025). SPA: A poisoning attack
framework for graph neural networks through searching and pairing. Machine
Learning, 114(1), 14.
MacKay, D. J., & Neal, R. M. (1997). Near Shannon limit performance of low-density parity
check codes. Electronics letters, 33(6), 457-458.
Patil, M. V., Pawar, S., & Saquib, Z. (2020). Coding techniques for 5G networks: A review.
In 2020 3rd International Conference on Communication System, Computing and IT
Applications (CSCITA) (pp. 208-213). IEEE.
Shannon, C. E. (1948). A mathematical theory of communication. The Bell system technical
journal, 27(3), 379-423.
Subhi, M. I., Al-Doori, Q., & Alani, O. (2023). Enhancing Data Communication Performance: A
Comprehensive Review and Evaluation of LDPC Decoder Architectures. Ingénierie des
Systèmes d'Information, 28(5).
Sun, S., Adachi, K., Tan, P. H., Zhou, Y., Joung, J., & Ho, C. K. (2015). Heterogeneous network:
An evolutionary path to 5G. In 2015 21st Asia-Pacific Conference on Communications
(APCC) (pp. 174-178). IEEE.
Tanner, R. (1981). A recursive approach to low complexity codes. IEEE Transactions on
information theory, 27(5), 533-547.
Xu, J., Yang, C., & Yuan, Y. (2023). Channel Coding in 5G New Radio. CRC Press.
Wu, X., Song, Y., Jiang, M., Zhao, C. (2010). Adaptivenormalized/offset min-sum algorithm.
Communications
Letters,
14(7):
667-669.
https://doi.org/10.1109/LCOMM.2010.07.100508.
Xu, M., Wu, J., Zhang, M. (2010). A modified offset min-sum decoding algorithm for LDPC
codes. In 3rd International Conference on Computer Science and Information
Technology, Chengdu, China, pp. 19-22. https://doi.org/10.1109/ICCSIT.2010.5564884
Zarubica R., Hinton R., Wilson S.G., Hall E.K. (2008) Efficient quantization schemes for LDPC
decoders, MILCOM 2008-2008 IEEE Military Communications Conference, San Diego,
CA, USA, pp. 1-5. https://doi.org/10.1109/MILCOM.2008.4753231