Detecção de Colisões e Priorização no Acesso Aleatório mMTC Inteligentes em Redes Celulares IoT
Resumo
O crescimento de aplicações de Internet das Coisas (IoT) em cenários de comunicações massivas do tipo machine-type communications (mMTC) impõe desafios significativos aos procedimentos de acesso aleatório em redes celulares. Em particular, a elevada ocorrência de colisões no canal de acesso aleatório (PRACH) compromete a eficiência do sistema, resultando em aumento da latência de acesso e no número de retransmissões. Este trabalho propõe uma abordagem integrada para detecção explícita de colisões baseada em aprendizado de máquina, combinada com políticas de priorização conscientes de colisão no procedimento de acesso aleatório. O modelo proposto é treinado a partir de dados simulados e otimizado para execução em ambientes de borda por meio de técnicas de quantização. Avaliações experimentais em cenários mMTC com até 30 mil dispositivos simultâneos demonstram reduções significativas na latência de acesso e no número médio de retransmissões, evidenciando o potencial da abordagem para redes celulares IoT de alta densidade.Referências
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Astudillo, C. A., de Andrade, T. P. C., and da Fonseca, N. L. S. (2017a). Allocation of control resources with preamble priority awareness for human and machine type communications in lte-advanced networks. In 2017 IEEE International Conference on Communications (ICC), pages 1–6.
Astudillo, C. A., de Andrade, T. P. C., and da Fonseca, N. L. S. (2017b). Impact of preamble-priority-aware downlink control signaling scheduling on lte/lte-a network performance. In 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), pages 1–5.
Bai, L., Han, R., Liu, J., Choi, J., and Zhang, W. (2020). Multiple delay estimation for collision resolution in non-orthogonal random access. IEEE Transactions on Vehicular Technology, 69(1):497–508.
De Andrade, T. P., Astudillo, C. A., Sekijima, L. R., and Da Fonseca, N. L. (2017). The random access procedure in long term evolution networks for the internet of things. IEEE Communications Magazine, 55(3):124–131.
Dudhe, P., Kadam, N., Hushangabade, R. M., and Deshmukh, M. S. (2017). Internet of things (iot): An overview and its applications. In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), pages 2650–2653.
Jang, H. S., Kim, S. M., Park, H.-S., and Sung, D. K. (2017). An early preamble collision detection scheme based on tagged preambles for cellular m2m random access. IEEE Transactions on Vehicular Technology, 66(7):5974–5984.
Jang, H. S., Kim, S. M., Park, H.-S., and Sung, D. K. (2018). A preamble collision resolution scheme via tagged preambles for cellular iot/m2m communications. IEEE Transactions on Vehicular Technology, 67(2):1825–1829.
Jang, H. S., Lee, H., Quek, T. Q. S., and Shin, H. (2021). Deep learning-based cellular random access framework. IEEE Transactions on Wireless Communications, 20(11):7503–7518.
Jang, H. S., Yun, M., Kim, T., and Bang, I. (2024). Non-orthogonal resource scheduling with enhanced preamble detection method for cellular random access networks. ICT Express.
Ko, K. S., Kim, M. J., Bae, K. Y., Sung, D. K., Kim, J. H., and Ahn, J. Y. (2012). A novel random access for fixed-location machine-to-machine communications in ofdma based systems. IEEE Communications Letters, 16(9):1428–1431.
Liang, Y., Li, X., Zhang, J., and Ding, Z. (2017). Non-orthogonal random access (nora) for 5g networks.
Linkous, L., Zohrabi, N., and Abdelwahed, S. (2019). Health monitoring in smart homes utilizing internet of things. In 2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), pages 29–34.
Magrin, D., Pielli, C., Stefanović, , and Zorzi, M. (2019). Enabling lte rach collision multiplicity detection via machine learning. In 2019 International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOPT), pages 1–8.
Mahbub, M. and Barua, B. (2021). Optimal radio resource allocation in small cells for a massive iot network: An mmtc perspective. In 2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), pages 01–04.
Narayanan, S., Tsolkas, D., Passas, N., and Merakos, L. (2018). Nb-iot: A candidate technology for massive iot in the 5g era. In 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), pages 1–6.
Wang, Y., Wang, T., Yang, Z., Wang, D., and Cheng, J. (2020). Throughput-oriented non-orthogonal random access scheme for massive mtc networks. IEEE Transactions on Communications, 68(3):1777–1793.
Wei, C., Bianchi, G., and Cheng, R. (2015). Modeling and analysis of random access channels with bursty arrivals in ofdma wireless networks. IEEE Transactions on Wireless Communications, 14(4):1940–1953.
Yin, Y., Zhao, D., Li, X., and Zeng, S. (2023). Learning based preamble collision detection of cellular random access by physical layer features. In 2023 International Conference on Networking and Network Applications (NaNA), pages 28–33, Los Alamitos, CA, USA. IEEE Computer Society.
Zhang, N., Kang, G., Wang, J., Guo, Y., and Labeau, F. (2015). Resource allocation in a new random access for m2m communications. IEEE Communications Letters, 19(5):843–846.
Publicado
25/05/2026
Como Citar
CÁRDENAS, Giancarlo Maldonado; TRUJILLO, Carlos A. Astudillo; FONSECA, Nelson L. S. da.
Detecção de Colisões e Priorização no Acesso Aleatório mMTC Inteligentes em Redes Celulares IoT. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 44. , 2026, Praia do Forte/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 230-239.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc_estendido.2026.19684.
