Joint aerial base station placement and user association for aerial-terrestrial networks: A whale optimization approach

被引:0
作者
Chin, Yong Hao [1 ]
Jiang, Shengqi [1 ]
Lee, Ying Loong [1 ]
Tee, Yee Kai
Chen, Chen [2 ]
Sheraz, Muhammad [3 ]
Chuah, Teong Chee [3 ]
Chang, Yoong Choon [1 ]
机构
[1] Univ Tunku Abdul Rahman, Lee Kong Chian Fac Engn & Sci, Jalan Sungai Long, Kajang 43000, Selangor, Malaysia
[2] Xidian Univ, Sch Telecommun Engn, Taibai South Rd, Xian 710071, Shaanxi, Peoples R China
[3] Multimedia Univ, Fac Engn, Persiaran Multimedia, Cyberjaya 63100, Selangor, Malaysia
关键词
Aerial base station placement; User association; Whale optimization algorithm; Multi-objective optimization; Greedy algorithm; UAV; ALLOCATION; POWER;
D O I
10.1016/j.adhoc.2025.103836
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Aerial-terrestrial networks have been envisaged as a key feature of sixth generation (6G) communications to resolve the capacity and coverage issues of the existing terrestrial ground base stations (GBSs) via unmanned aerial vehicle-mounted base stations (ABSs). However, with the introduction of ABSs into the mobile networks, load balancing among ABSs becomes more challenging, as it additionally requires careful placement of ABSs in the three-dimensional (3D) airspace for coverage provisioning. Also, user quality of service (QoS) requirements and interference between ABSs and GBSs require meticulous management during the user association process for effective load balancing. In this paper, we propose a new joint ABS placement and user association scheme based on a whale optimization algorithm (WOA) for throughput maximization and load balancing in aerial- terrestrial networks. Firstly, a multi-objective ABS placement and user association problem is formulated for an aerial-terrestrial network to jointly maximize an alpha-fairness-based load balancing utility function and the network throughput. Then, we develop a WOA algorithmic framework to solve the multi-objective problem, with each whale representing a candidate ABS placement solution, whose optimality is evaluated using a fitness function designed based on network throughput maximization and physical isolation constraints. Also, a QoS-aware greedy user association algorithm that maximizes the load balancing utility function is developed to facilitate the fitness evaluation of each whale. Simulation results show that the proposed scheme outperforms several state-of-the-art schemes in terms of Jain's fairness index, probability of blocking and total throughput.
引用
收藏
页数:12
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