Joint Aerial Base Station Placement and User Association for Latency-Driven Load Balancing in Aerial Mobile Networks
The use of aerial base stations (ABSs) has gained significant interest due to their deployment flexibility for coverage and capacity enhancements. However, the load balancing problem in multi-ABS networks, which is crucial for quality of service (QoS) provisioning and fair ABS utilization, remains largely unresolved. This paper investigates the load balancing problem for multi-ABS networks with consideration of backhaul limitations, while taking into account the delay-QoS performance of the networks. Firstly, we quantify the load of each ABS with the effective capacity (EC), which is characterized by a latency parameter known as the delay-QoS exponent. Then, we design a load balancing utility function based on the generalized α-fairness concept, which provides the flexibility to the network to achieve various degrees of load balance among ABSs. Next, a joint ABS placement and user association problem is formulated with the aim to maximize the load balancing utility function, with consideration of backhaul capacity constraints, physical isolation between ABSs and ABSs’ limited user capacity. Since the problem is a mixed-integer programming problem which is generally difficult to solve optimally, we develop an efficient solution framework, which optimizes the 3D placements of ABSs using swarm intelligence and user association via convex optimization. Simulation results show that our proposed scheme outperforms existing schemes in terms of load balance, probability of blocking, and EC.
Authors
- Mau‐Luen Tham (ORCID: https://orcid.org/0000-0003-4600-9839)
- Yoong Choon Chang (ORCID: https://orcid.org/0000-0002-4065-1639)
- Ying Loong Lee (ORCID: https://orcid.org/0000-0002-0841-449X)
- Donghong Qin
- Shengqi Jiang
- Yee Kai Tee (ORCID: https://orcid.org/0000-0002-0263-6358)
- Chenxi Li (ORCID: https://orcid.org/0000-0002-9106-8048)
Institutions
- Xidian University (CN)
- Guangxi University (CN)
- Universiti Tunku Abdul Rahman (MY)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-10-03
- DOI
- https://doi.org/10.1109/jiot.2025.3617469
- Primary Topic
- Indoor and Outdoor Localization Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00