Optimization of UAV Heading for the Ground-to-Air Uplink
Feng Jiang, A. Lee Swindlehurst

TL;DR
This paper develops algorithms for dynamically adjusting UAV heading to optimize uplink communication rates in ground-to-air wireless systems, demonstrating significant performance gains through simulations.
Contribution
It introduces a novel algorithm for UAV heading adjustment to maximize uplink sum rate, incorporating mobility tracking and asymptotic analysis for different channel conditions.
Findings
Adaptive heading adjustment improves sum rate performance.
Simplified algorithms perform near-optimally in simulations.
Algorithm effectively tracks mobile ground nodes for dynamic optimization.
Abstract
In this paper we consider a collection of single-antenna ground nodes communicating with a multi-antenna unmanned aerial vehicle (UAV) over a multiple-access ground-to-air wireless communications link. The UAV uses beamforming to mitigate the inter-user interference and achieve spatial division multiple access (SDMA). First, we consider a simple scenario with two static ground nodes and analytically investigate the effect of the UAV heading on the system sum rate. We then study a more general setting with multiple mobile ground-based terminals, and develop an algorithm for dynamically adjusting the UAV heading in order to maximize a lower bound on the ergodic sum rate of the uplink channel, using a Kalman filter to track the positions of the mobile ground nodes. Fairness among the users can be guaranteed through weighting the bound for each user's ergodic rate with a factor inversely…
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Taxonomy
TopicsUAV Applications and Optimization · Cooperative Communication and Network Coding · Advanced MIMO Systems Optimization
