Optimizing Data Transmission in 5G Networks for Low Latency and High Reliability

  • Authors

    • Kenji Sato Engineering Director, Sony Corporation, Japan Author

    DOI:

    https://doi.org/10.67228/30716357/IJMRSE-2018PI2B7R

    Published 04-04-2018

  • 5G Networks, Data Transmission Optimization, Low Latency, High Reliability, Network Slicing, URLLC, AI-Driven Network Management, Edge Computing, Adaptive Modulation, Spectrum Efficiency

    Issue

    Vol. 1 No. 1 (2018)

    Section

    Articles

    How to Cite

    Optimizing Data Transmission in 5G Networks for Low Latency and High Reliability. (2018). International Journal of Modern Research in Science & Engineering, 1(1), 01-10. https://doi.org/10.67228/30716357/IJMRSE-2018PI2B7R

  • Abstract

    The rapid advancement of wireless communication has led to the emergence of the fifth-generation (5G) network, which aims to provide ultra-reliable low-latency communication (URLLC) while ensuring high data transmission rates. Optimizing data transmission in 5G networks is critical for supporting real-time applications such as autonomous vehicles, telemedicine, industrial automation, and smart cities. This paper explores various techniques and strategies to enhance data transmission efficiency, minimize latency, and improve reliability in 5G networks. We analyze the key performance indicators (KPIs) that influence data transmission, including bandwidth utilization, network slicing, and multiple access techniques. Furthermore, we discuss the role of edge computing, artificial intelligence (AI)-driven network management, and adaptive modulation techniques in optimizing data transmission. The paper also highlights the impact of interference management, energy efficiency considerations, and security protocols on 5G network performance. We conduct a comprehensive literature survey to examine existing optimization techniques and propose an improved methodology leveraging AI-driven resource allocation and dynamic spectrum sharing. Through simulation and analytical results, we demonstrate the effectiveness of the proposed approach in reducing end-to-end latency and improving network reliability. The findings contribute to the ongoing efforts in optimizing 5G networks and lay the foundation for future research in beyond-5G (B5G) and sixth-generation (6G) communication systems.

  • References

    [1] Shafi, M. et al., “5G: A Tutorial Overview of Standards, Trials, Challenges, Deployment, and Practice,” IEEE Journal on Selected Areas in Communications, vol. 35, no. 6, pp. 1201–1221, 2017.

    [2] Andrews, J. G. et al., “What Will 5G Be?” IEEE Journal on Selected Areas in Communications, vol. 32, no. 6, pp. 1065–1082, 2014.

    [3] Dahlman, Erik, Parkvall, Stefan, and Sköld, Johan, 5G NR: The Next Generation Wireless Access Technology, Academic Press, 2018.

    [4] Popovski, Petar et al., “Wireless Access for Ultra-Reliable Low-Latency Communication: Principles and Building Blocks,” IEEE Network, vol. 32, no. 2, pp. 16–23, 2018.

    [5] Bennis, Mehdi, Debbah, Merouane, and Poor, H. Vincent, “Ultra-Reliable and Low-Latency Wireless Communication: Tail, Risk, and Scale,” Proceedings of the IEEE, vol. 106, no. 10, pp. 1834–1853, 2018.

    [6] Taleb, Tarik et al., “On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Architecture,” IEEE Communications Surveys & Tutorials, vol. 19, no. 3, pp. 1657–1681, 2017.

    [7] Zhang, Ning et al., “Ultra-Reliable and Low-Latency Communication in 5G Networks,” IEEE Communications Magazine, vol. 56, no. 12, pp. 52–58, 2018.

    [8] Parkvall, Stefan et al., “NR: The New 5G Radio Access Technology,” IEEE Communications Standards Magazine, vol. 1, no. 4, pp. 24–30, 2017.

    [9] Osseiran, Afif et al., “Scenarios for 5G Mobile and Wireless Communications: The Vision of the METIS Project,” IEEE Communications Magazine, vol. 52, no. 5, pp. 26–35, 2014.

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