Wireless coverage using unmanned aerial vehicles

The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civilian application domains including real-time monitoring, search and rescue, and wireless coverage. UAVs can be used to provide wireless coverage during emergency cases where each UAV serves as an aerial wireless base station when the cellular network goes down. They can also be used to supplement the ground base station in order to provide better coverage and higher data rates for the users. During such situations, the UAVs need to return periodically to a charging station for recharging, due to their limited battery capacity. Given the recharging requirements, the problem of minimizing the number of UAVs required for a continuous coverage of a given area is first studied in this dissertation. Due to the intractability of the problem, partitioning the coverage graph into cycles that start at the charging station is proposed and the minimum number of UAVs to cover such a cycle is characterized based on the charging time, the traveling time and the number of subareas to be covered by a cycle. Based on this analysis, an efficient algorithm is proposed to solve the problem. In the second part of this dissertation, the problem of optimal placement of a single UAV is studied, where the objective is to minimize the total transmit power required to provide wireless coverage for indoor users. Three cases of practical interest are considered and efficient solutions to the formulated problem under these cases are presented. Due to the limited transmit power of a UAV, the problem of minimizing the number of UAVs required to provide wireless coverage to indoor users is studied and an efficient algorithm is proposed to solve the problem. In the third part of this dissertation, the problem of maximizing the indoor wireless coverage using UAVs equipped with directional antennas is studied. The case that the UAVs are using one channel is considered, thus in order to maximize the total indoor wireless coverage, the overlapping in their coverage volumes is avoided. Two methods are presented to place the UAVs; providing wireless coverage from one building side and from two building sides. The results show that the upside-down arrangements of UAVs can improve the total coverage by 100% compared to providing wireless coverage from one building side. In the fourth part of this dissertation, the placement problem of UAVs is studied, where the objective is to determine the locations of a set of UAVs that maximize the lifetime of wireless devices. Due to the intractability of the problem, the number of UAVs is restricted to be one. Under this special case, the problem is formulated as a convex optimization problem under a restriction on the coverage angle of the ground users and a gradient projection based algorithm is proposed to find the optimal location of the UAV. Based on this, an efficient algorithm is proposed for the general case of multiple UAVs. The problem of minimizing the number of UAVs required to serve the ground users such that the time duration of uplink transmission of each wireless device is greater than or equal to a threshold value is also studied. Two efficient methods are proposed to determine the minimum number of UAVs required to serve the wireless devices

Optimal Deployments of UAVs With Directional Antennas for a Power-Efficient Coverage

To provide a reliable wireless uplink for users in a given ground area, one can deploy Unmanned Aerial Vehicles (UAVs) as base stations (BSs). In another application, one can use UAVs to collect data from sensors on the ground. For a power-efficient and scalable deployment of such flying BSs, directional antennas can be utilized to efficiently cover arbitrary 2-D ground areas. We consider a large-scale wireless path-loss model with a realistic angle-dependent radiation pattern for the directional antennas. Based on such a model, we determine the optimal 3-D deployment of N UAVs to minimize the average transmit-power consumption of the users in a given target area. The users are assumed to have identical transmitters with ideal omnidirectional antennas and the UAVs have identical directional antennas with given half-power beamwidth (HPBW) and symmetric radiation pattern along the vertical axis. For uniformly distributed ground users, we show that the UAVs have to share a common flight height in an optimal power-efficient deployment. We also derive in closed-form the asymptotic optimal common flight height of $N$ UAVs in terms of the area size, data-rate, bandwidth, HPBW, and path-loss exponent

Control of an indoor autonomous mobile communications relay via antenna diversity

Presented in this thesis is a motion planning scheme for enabling a quadrotor unmanned aerial vehicle (UAV) to serve as an autonomous communications relay in indoor or GPS-denied environments. The goal of the algorithm is to maximize the throughput of the end-to-end communications channel. An extremum-seeking controller steers the quadrotor while collision avoidance is provided by artificial potential fields. Extremum-seeking is model-free adaptive control method; it\u27s applicable in situations where there is a nonlinearity in the control problem and the nonlinearity has a local minimum or maximum. The extremum-seeking controller presented here is driven by antenna diversity and attempts to optimize the inputs to an unknown, time-varying cost function characterized by the RF environment. Each of the multiple antennas onboard the quadrotor receives the same incoming packets and provides associated signal strength measurements. The extremum-seeking controller then uses these measurements to autonomously fly the quadrotor communications relay to an optimal location so as to maximize throughput, all without positioning data. This work is motivated by the need to extend the operating ranges of robots in complex urban and indoor environments. The algorithm and necessary technical background are presented in detail. Simulations results verify the validity of the proposed extremum-seeking approach. Experiments demonstrate the feasability of implementing the extremum-seeking controller with tangible hardware