首页|Burst Traffic Demand Based Adaptive Network Planning and Optimization Approach for 5G/6G Network
Burst Traffic Demand Based Adaptive Network Planning and Optimization Approach for 5G/6G Network
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NETL
NSTL
IEEE
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.
Autonomous aerial vehiclesSignal to noise ratioOptimizationInterferencePlanningOptimization modelsClustering algorithmsDisastersCostsComplexity theory
Yiyun Guo、Yaqin Xie
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Changwang School of Honors, Nanjing University of Information Science and Technology, Nanjing, China
School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China
NETL
NSTL
IEEE
