Dynamic Resource Allocation for Differentiated Service Adaptation in FANET
Zhuojia Yang, Bin Yang, Wei Su, Yudong Ma, Yihua Peng, Qi Liu, Peng Liang · 2024
Unmanned Aerial Vehicles (UAVs)-aided Flying Adhoc Networks (FANETs) are critical to providing emergency communications in disaster scenarios. A fundamental issue is to allocate limited resources while satisfying the requirements of various delay-sensitive urgent services in such networks. To this end, this paper investigates dynamic resource allocation for differentiated service adaptation in FANETs. We first introduce a two-dimension time-frequency resource mapping method to represent the wireless resources. We then propose a Partial-Ensuring Modulation and Time-Frequency Resource Allocation (PE-MTFA) algorithm to optimize resource allocation with the constraint of the acceptable signal-to-noise ratio (SNR) thresholds for different modulation formats. We further propose a Differentiated-Adaptive Modulation and Time-Frequency Resource Allocation (DA-MTFA) algorithm to ensure different transmission priorities for differentiated rescue services. Simulation results are provided to validate the effectiveness of PE-MTFA and DA-MTFA algorithms in allocating resources dynamically under UAV-aided FANETs and also indicate that DA-MTFA outperforms PE-MTFA in terms of overall service blocking probability and the proportion of high-priority services among blocked services.