Optimal position seeking for unmanned aerial vehicle communication relay using only signal strength and angle of arrival

Abstract

This paper investigates the problem of communication relay between ground units using an unmanned aerial vehicle (UAV). The positions of the ground units are considered to be unavailable to the UAV and the objective is to drive the vehicle in real-time to the optimal placement maximizing the strength of communication signals from ground units. To this end, a novel non model-based navigation law is proposed that is solely based on signals strength and their angles of arrival. The stability of the proposed navigation law is proved in two scenarios, driving the UAV to the optimal placement and returning it back to the launch base. Simulation and experimental results are given to show the effectiveness of the proposed approach.

Efficient Local Map Search Algorithms for the Placement of Flying Relays

“…In [8]- [16], the path loss was modeled as a deterministic function of the UAV-to-user distance, irrelevant to specific UAV positions. Thanks to the simplicity of these distance-based models, [8]- [12] developed solutions to UAV navigation problems, [13] studied optimization strategies for multiple-input multipleoutput (MIMO) communications with UAVs with multiple antennas, and [14] optimized the UAV position for cooperative communications. The models used in [8]- [16] imply that the path loss is the same under the same distance, but more detailed research in [17], [18] suggests that air-to-ground propagation should also depend on the elevation angle of the UAV-user link.…”

“…In addition, we discuss optimality for continuous-time algorithm trajectory x(t), which can be obtained from Algorithm 1 using infinitesimal step size δ = O(dt) at each infinitesimal time slot dt. Specifically, the search trajectory x(t) in Algorithm 1 can be described by piece-wise continuous dynamic systems, where one replaces δ by κdt in (12) and γ by κγdt in (13), in which κ is a parameter that specifies the moving speed of the UAV. Accordingly, the continuous-time processes of the minimum cost F min (t) and the position track record x(t) are given by F min (t) = minimize 0≤τ ≤t f (g u (x(τ ), g b (x(τ )) and x(t) = x(τ ), respectively, where τ = arg min 0≤τ ≤t f (g u (x(τ ), g b (x(τ )).…”

Position optimisation for multiple mobile relays by utilising one‐bit feedback information

“…There are two approaches for working with such unpractical assumptions, i.e. perturbation‐based extreme seeking control [6, 7] and multiple on‐board antennas [8–10]. In the former approach, the strength of the received signal at the destination node is measured to determine whether it meets the system requirement, and the result with complete information is continually fed back to the mobile relay for optimising the position of the mobile relay.…”