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A Two‐Stage Resource Allocation Algorithm for Priority‐Aware QoS Optimization in LTE Networks

Jul 2026 · International Journal of Communication Systems · Vol 39 · 0 citations · 10 references

TL;DR

An innovative resource allocation scheme tailored for various services in the downlink of LTE systems is presented, emphasizing service differentiation as a vital factor for QoS, particularly for real‐time traffic.

Abstract

As mobile cellular communication technology advances and wireless mobile devices become increasingly popular, multimedia applications have become essential in modern society. Long‐term evolution (LTE), launched in 2009, has established itself as a leading cellular technology by providing high‐speed data and media transport. Its successor, LTE‐Advanced (LTE‐A), further enhances this capability with greater bandwidth and peak data rates, enabling effective multimedia transmission beyond traditional voice communication. To ensure consumer satisfaction, high quality of service (QoS) is critical. This paper presents an innovative resource allocation scheme tailored for various services in the downlink of LTE systems, emphasizing service differentiation as a vital factor for QoS, particularly for real‐time traffic. We provide a comprehensive overview of LTE architecture, its components, and their interconnections, followed by an in‐depth discussion of resource allocation, scheduling techniques, and QoS mechanisms in LTE. Furthermore, we review existing studies and algorithms, leading to the introduction of our proposed Two‐stage resource allocation with user satisfaction (TSRAUS) algorithm. Key findings demonstrate that the TSRAUS algorithm significantly improves resource utilization and user experience by effectively managing priorities between real‐time and nonpriority applications. Comprehensive statistical analysis, including confidence intervals and significance tests, rigorously validates the TSRAUS algorithm's superior performance across key QoS metrics. The conclusion summarizes these findings and highlights potential future enhancements, including the extension of the algorithm to multicell scenarios, user mobility considerations, and adaptive mechanisms to better address evolving network demands.

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