Research on a load balancing algorithm based on utility function in UAV-assisted networks
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1. Department of Electronic and Communication Engineering, North China Electric Power University, Baoding 071003, China 2. Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University, Baoding 071003, China

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TN929.53

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    Abstract:

    UAV plays an important role in wireless networks due to the advantages of high mobility and high line-of-sight communication probability. However, in a multi-UAV system, the traditional user association method cannot meet the on-demand deployment of UAV, and there is a problem that the load is imbalanced. To this end, a utility function is first constructed, which comprehensively considers three factors: the user's received signal-to-interference-to-noise ratio, the UAV’s load, and the spatial dispersion of the set of users served by the same UAV. Second, network load balancing is achieved by solving the utility maximization problem. In order to solve this mixed integer nonlinear non-convex problem, a load balancing algorithm based on utility function is proposed, which decomposes the original problem into two sub-problems of user association and UAV location optimization for iterative solution. Given the location of the UAV, a user association algorithm based on the maximum utility is proposed to obtain the best user association scheme. Based on the current best user association scheme, an improved distributed ordinal location optimization algorithm is proposed to obtain the best UAV location. Finally, by solving the user association and UAV location optimization sub-problems iteratively, the optimal user association scheme and UAV location can be obtained. The simulation results show that the proposed algorithm improves the load balancing level by 52.56% and 7.63% respectively compared with the maximum SINR association method and the "maximum SINR+UAV location optimization" method, which has the advantage of significantly improving the load balancing effect.

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  • Received:
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  • Online: May 14,2024
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