Radio Map Enabled Path Planning for Multiple Cellular-Connected Unmanned Aerial Vehicles

ZHOU Decheng; WANG Wei; SHAO Xiang; CHEN Mei; XIAO Jianghao

doi:10.11999/JEIT250821

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ZHOU Decheng, WANG Wei, SHAO Xiang, CHEN Mei, XIAO Jianghao. Radio Map Enabled Path Planning for Multiple Cellular-Connected Unmanned Aerial Vehicles[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250821

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ZHOU Decheng, WANG Wei, SHAO Xiang, CHEN Mei, XIAO Jianghao. Radio Map Enabled Path Planning for Multiple Cellular-Connected Unmanned Aerial Vehicles[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250821

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Radio Map Enabled Path Planning for Multiple Cellular-Connected Unmanned Aerial Vehicles

doi: 10.11999/JEIT250821 cstr: 32379.14.JEIT250821

1.
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2.
School of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an 710049, China
3.
China Telecom Corporation Limited Jiangsu Branch, Nanjing 210037, China

Funds: The National Natural Science Foundation of China (62371231), The Natural Science Foundation on Frontier Leading Technology Basic Research Project of Jiangsu (BK20222001), Jiangsu Provincial Key Research and Development Program (BE2023027)

Received Date: 2025-08-29
Accepted Date: 2025-12-22
Rev Recd Date: 2025-12-22

Available Online: 2026-01-03

Abstract

Abstract

Objective In collaborative operation scenarios of cellular-connected Unmanned Aerial Vehicles (UAVs), conflict avoidance strategies often cause unbalanced service quality. Traditional schemes focus on reducing total task completion time but do not ensure service fairness. To address this issue, a radio map-assisted cooperative path planning scheme is proposed. The objective is to minimize the maximum weighted sum of task completion time and communication disconnection time across all UAVs to improve service fairness in multi-UAV scenarios. Methods A Signal-to-Interference-plus-Noise Ratio (SINR) map is constructed to assess communication quality. The two-dimensional airspace is discretized into grids, and link gain maps are generated through ray tracing and Axis-Aligned Bounding Box detection to determine Line-of-Sight (LoS) or Non-Line-of-Sight (NLoS) conditions. The SINR map is produced by selecting, for each grid, the base station with the highest expected SINR. To solve the optimization problem, an Improved Conflict-Based Search (ICBS) algorithm with a hierarchical structure is developed. At the high-level stage, proximity conflicts are managed to maintain safety distances, and the cost function is reformulated to emphasize fairness by minimizing the maximum weighted time. The low-level stage applies a bidirectional A* algorithm for single-UAV path planning, using parallel search to improve efficiency while meeting the constraints set by the high-level stage. Results and Discussions The proposed scheme is evaluated through simulations across different scenarios. Building heights and positions are shown, where base station locations are marked by red stars and building heights are represented with color gradients from light to dark to indicate increasing height (Fig. 2). The wireless propagation characteristics between UAVs and ground base stations are demonstrated by the SINR map at an altitude of 60 m (Fig. 3), which shows significant SINR degradation in areas affected by building blockage and co-channel interference, resulting in communication blind zones. Trajectory planning results for four UAVs at an altitude of 60 m with a SINR threshold of 2 dB show that all UAVs avoid signal blind zones and complete tasks without collision risks under the proposed scheme (Fig. 4). The trade-off between task completion time and disconnection time is controlled by the weight coefficient (Fig. 5). The maximum weighted time increases monotonically as the weight coefficient increases, whereas the maximum disconnection time decreases. The bidirectional A* algorithm achieves higher computational efficiency than Dijkstra’s and traditional A* algorithms while maintaining optimal solution quality (Table 1). All three algorithms yield identical weighted times, confirming the optimality of the bidirectional A* approach, and its runtime is reduced significantly due to parallel search. Compared with three benchmark schemes, the proposed scheme achieves the lowest maximum weighted time for different SINR thresholds (Fig. 6). Performance analysis at different UAV altitudes shows that the proposed scheme maintains stable maximum weighted time below 75 m, while sharp increases appear above 75 m due to intensified interference from non-serving base stations (Fig. 7). The scalability analysis further shows clear improvements over benchmark schemes, especially when conflicts occur more frequently (Fig. 8). Conclusions To address fairness in cellular-connected multi-UAV systems, a radio map-assisted path planning scheme is proposed to minimize the maximum weighted time. Based on a discretized SINR map, an ICBS algorithm is developed. At the high-level stage, proximity conflicts and a reformulated cost function ensure safety and fairness, and at the low-level stage, a bidirectional A* algorithm increases search efficiency. Simulation results show that the proposed scheme lowers the maximum weighted time compared with benchmark schemes and improves fairness and overall multi-UAV collaboration performance.
- Cellular-connected UAV,
- Radio map,
- Path planning,
- Conflict-based search algorithm

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References(27)

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