Bridging the technology divide for mobile traffic management & improving network performance
*Vikas GuptaCorresponding authorvikasismailed@gmail.comDepartment of Computer Science and EngineeringSharda School of Computing Science & EngineeringSharda UniversityGreater Noida, Uttar Pradesh, 201310, IndiaView full profile → , Pushpendra Kumar Rajputpushpendrarajputs@gmail.comDepartment of Computer Science and EngineeringSharda School of Computing Science & EngineeringSharda UniversityGreater Noida, Uttar Pradesh, 201310, IndiaView full profile → , Manoj Kumarwssmanojkumar@gmail.comDepartment of Engineering and Information ScienceSchool of Computer ScienceUniversity of WollongongDubai, 20183, United Arab EmiratesView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Dec 2025
- Published Online:
- 30 Sep 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2415
- Pages:
- 3193–3206
Abstract
While fourth generation (4G) network is taking shape in all existing mobile networks & alongside on a worldwide scale the fifth generation (5G) network is expanding quickly. The rapid development of the Internet of Things (IoT) and innovations in technological advancements have culminated in production of an enormous amount of data. The degree of quality of service (QoS) of vertical sectors is significantly affected by network coverage and scalability. One of the most important and vital measures when evaluating a network’s performance is its capacity and coverage capability. However, the precision of the current techniques and systems’ monitoring important indicators of performance and results is inadequate for rapid results. To enable it to more properly rebuild the current state of 4G and 5G systems, parametric optimization, in this investigation, we build an analysis approach & parametric study of optimization and enhancement of mobile network key performance indicators and service parameters, evaluating them and implement an integrated analysis strategy. Those action results indicate the impact of correcting various parameters yielding the network element throughputs to their optimum capabilities, capacity & excellent performance results of service indicators. In conjunction with this, we present a meaningful evaluation of the industrial network, which confirms the viability of the methods adopted for network optimization & helping effectively through detecting hidden bottlenecks of network element capacity & weak user perception, boosting the 5G experience for users along with providing additional suggestions for future 5G building. The approach recommended is widely feasible and can be applied to multi-frequency, multi-operator, or even further generation in technological advancement in sixth–generation (6G) networks.
Traditional Network planning and parameters optimization methods are no longer an option to take mobile networks to their highest performance levels. In the past, desktop-based planning with disconnected tools and maps might have been sufficient. For 5G networks, it is no longer a viable option because of the increased complexity - for example, there are countless traffic volume transactions, Network Traffic congestion & controls, end to end effective quality of service, possible beamforming patterns, propagation-sensitive mm Wave radios and frequent software updates. In order to alleviate traffic congestion, traffic management & optimizing control systems are an important tool. These systems strive to boost the efficiency of mobile network to optimize traffic flow on individual network interfaces. The process takes significant CORE, IPTX & RF wisdom and robust analytics, to reach optimal network performance right from the beginning for geographical analysis.
Finally, in this study, through KPI (Key performance indicator) correlation, parametric analysis & traffic management of different interfaces, the mobile operator can test and verify the impact and optimize the network capabilities and quality before deployment of services either in hardware or software form. It also supports to enhance network & user perception both & also helps in driving & improving Operational expenditures & Capital expenses & savings.
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References
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