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We consider multiple unmanned aerial vehi- cles (UAVs) serving a density of ground terminals (GTs) as mobile base stations. The objective is to minimize the outage probability of GT-to-UAV transmissions. In this context, the optimal placement of UAVs under different UAV altitude constraints and GT densities is studied. First, using a random deployment argument, a general upper bound on the optimal outage probability is found for any density of GTs and any number of UAVs. Lower bounds on the performance of optimal deployments are also deter- mined. The upper and lower bounds are combined to show that the optimal outage probability decays exponentially with the number of UAVs for GT densities with finite support. Next, the structure of optimal deployments are studied when the common altitude constraint is large. In this case, for a wide class of GT densities, it is shown that all UAVs should be placed to the same location in an optimal deployment. A design implication is that one can use a single multi-antenna UAV as opposed to multiple single-antenna UAVs without loss of optimality. Numerical optimization of UAV deployments are carried out using particle swarm optimization. Simulation results are also presented to confirm the analytical findings.
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ECHO: Empirical Characterization and Height Optimization of UAV-to-Underground Channels
This paper explores the nexus of two emerging Internet of Things (IoT) components in precision agriculture, which requires vast amounts of agriculture fields to be monitored from air and soil for food production with efficient resource utilization. On the one hand, unmanned aerial vehicles (UAVs) have gained interest in agricultural aerial inspection due to their ubiquity and observation scale. On the other hand, agricultural IoT devices, including buried soil sensors, have gained interest in improving natural resource efficiency in crop production. In this work, the path loss and fading characteristics in wireless links between a UAV and underground (UG) nodes (Air2UG link) are studied to design a UAV altitude optimization solution. A path loss model is developed for the Air2UG link, including fading in the channel, where fading is modeled using a Rician distribution and validated using the Kolmogorov-Smirnov test. Moreover, Rician-K is found to be dependent on the UAV altitude, which is modeled with a Gaussian function with an RMSE of 0.4-1.3 dB. Furthermore, a novel altitude optimization solution is presented to minimize the bit error rate (BER). Results show that the lowest possible altitude does not always minimize the BER. Optimizing the altitude reduces the Air2UG link BER by as much as 8.6-fold. Likewise, altitude optimization can minimize the impacts of increasing burial depth on the BER. Our results and analysis are the first in this field and can be exploited to optimize the altitude and resources of a UAV node to communicate with the sensors embedded in the soil efficiently.
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- PAR ID:
- 10434923
- Date Published:
- Journal Name:
- IEEE IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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