Burst Traffic Demand Based Adaptive Network Planning and Optimization Approach for 5G/6G Network

To support the long-term stable communication demand along with burst traffic demands in 5G/6G smart environments, a new hybrid deployment strategy for fixed base stations (BSs) and unmanned aerial vehicles (UAVs) is proposed. Firstly, a cell integration strategy based on user distribution is proposed, which addresses the issues of high algorithm complexity and poor stability associated with existing hybrid macro/micro BS deployments. Secondly, to tackle the problem of large-scale burst traffic demand that cannot be solely covered by fixed BSs, UAVs are deployed according to user traffic demand, thereby effectively enhancing network coverage and minimizing unnecessary overheads. Simulation results reveal that our approach enhances coverage by 38.45%, reduces algorithm complexity by 31.22%, and decreases UAV deployment costs by 8.9% compared to the traditional method, while ensuring over 98% coverage of burst traffic demand. Furthermore, it confirms that our method fulfills the requirements of mobile user scenarios.

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Publication Details

Journal
IEEE Communications Letters
Published
2025-02-03
DOI
https://doi.org/10.1109/lcomm.2025.3537863
Primary Topic
Telecommunications and Broadcasting Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Burst Traffic Demand Based Adaptive Network Planning and Optimization Approach for 5G/6G Network

Yaqin Xie, Yanchuan Guo
IEEE Communications Letters
Telecommunications and Broadcasting Technologies
article

Burst Traffic Demand Based Adaptive Network Planning and Optimization Approach for 5G/6G Network

Yaqin Xie, Yanchuan Guo
article en

Abstract

To support the long-term stable communication demand along with burst traffic demands in 5G/6G smart environments, a new hybrid deployment strategy for fixed base stations (BSs) and unmanned aerial vehicles (UAVs) is proposed. Firstly, a cell integration strategy based on user distribution is proposed, which addresses the issues of high algorithm complexity and poor stability associated with existing hybrid macro/micro BS deployments. Secondly, to tackle the problem of large-scale burst traffic demand that cannot be solely covered by fixed BSs, UAVs are deployed according to user traffic demand, thereby effectively enhancing network coverage and minimizing unnecessary overheads. Simulation results reveal that our approach enhances coverage by 38.45%, reduces algorithm complexity by 31.22%, and decreases UAV deployment costs by 8.9% compared to the traditional method, while ensuring over 98% coverage of burst traffic demand. Furthermore, it confirms that our method fulfills the requirements of mobile user scenarios.

IEEE Communications LettersVol. 29(5)
Nanjing University of Information Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 97%
Telecommunications and Broadcasting Technologies
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