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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM66107

Evaluating 5G Network Performance and Ultra-Low-Latency Communication: A Study of QoS and RedCap for Industrial IoT

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM66107

Volume:

10 |

7 |

Jul 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM66107

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Dr. Saima Aleem

Dr. Saima Aleem

Department of Computer Science Engineering

Khwaja Moinuddin Chishti Language University

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Dr Nasruddin

Department of Computer Science Engineering

Khwaja Moinuddin Chishti Language University

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Abstract

The deployment of 5G technology has commenced in India and other regions, aiming to facilitate higher data rates, reduced latency, and enhanced network capacity. Nonetheless, the nationwide implementation remains inconsistent, with service quality exhibiting considerable variation among operators and urban locales. This review evaluates 5G performance, particularly emphasizing ultra-low-latency communication by assessing round-trip latency, throughput, and packet loss through empirical drive tests and application-level observations. Additionally, the study explores 5G Reduced Capability (RedCap) devices as a crucial facilitator for industrial IoT, where it is imperative to minimize cost, power consumption, and hardware complexity while maintaining reliable connectivity. The paper underscores existing Quality of Service (QoS) deficiencies in 5G deployments and discusses the technical and policy interventions required to enhance latency-sensitive services in India.

KEYWORDS

5G ultra-low latency URLLC RedCap QoS industrial IoT network performance

Cite This Article

Dr. Saima Aleem, Dr Nasruddin, "Evaluating 5G Network Performance and Ultra-Low-Latency Communication: A Study of QoS and RedCap for Industrial IoT," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 7, pp. 1-4, Jul 2026. https://doi.org/10.55041/IJSREM66107

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References

1. Baldonado, M., Chang, C.-C.K., Gravano, L., Paepcke, A.: The Stanford Digital Library Metadata Architecture. Int. J. Digit. Libr. 1 (1997) 108–121 2. Bruce, K.B., Cardelli, L., Pierce, B.C.: Comparing Object Encodings. In: Abadi, M., Ito, T. (eds.): Theoretical Aspects of Computer Software. Lecture Notes in Computer Science, Vol. 1281.Springer-Verlag,BerlinHeidelbergNew York(1997) 415–438 3. van Leeuwen, J. (ed.): Computer Science Today. Recent Trends and Developments. Lecture Notes in Computer Science, Vol. 1000.Springer-Verlag,BerlinHeidelbergNew York(1995) 4. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. 3rd edn.Springer-Verlag,BerlinHeidelbergNew York(1996)    

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Publication Date

7/17/2026

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