51,576 research outputs found

    Multicell Edge Coverage Enhancement Using Mobile UAV-Relay

    Get PDF
    Unmanned aerial vehicle (UAV)-assisted communication is a promising technology in future wireless communication networks. UAVs can not only help offload data traffic from ground base stations (GBSs) but also improve the Quality of Service (QoS) of cell-edge users (CEUs). In this article, we consider the enhancement of cell-edge communications through a mobile relay, i.e., UAV, in multicell networks. During each transmission period, GBSs first send data to the UAV, and then the UAV forwards its received data to CEUs according to a certain association strategy. In order to maximize the sum rate of all CEUs, we jointly optimize the UAV mobility management, including trajectory, velocity, and acceleration, and association strategy of CEUs to the UAV, subject to minimum rate requirements of CEUs, mobility constraints of the UAV, and causal buffer constraints in practice. To address the mixed-integer nonconvex problem, we transform it into two convex subproblems by applying tight bounds and relaxations. An iterative algorithm is proposed to solve the two subproblems in an alternating manner. Numerical results show that the proposed algorithm achieves higher rates of CEUs as compared with the existing benchmark schemes

    Design of an embedded microcomputer based mini quadrotor UAV

    Get PDF
    This paper describes the design and realization of a mini quadrotor UAV (Unmanned Aerial Vehicle) that has been initiated in the Systems and Control Laboratory at the Computer and Automation Research institute of the Hungarian Academy of Science in collaboration with control departments of the Budapest University of Technology and Economics. The mini quadrotor UAV is intended to use in several areas such as camera-based air-surveillance, traffic control, environmental measurements, etc. The paper focuses upon the embedded microcomputer-based implementation of the mini UAV, describes the elements of the implementation, the tools realized for mathematical model building, as well as obtains a brief outline of the control design

    The Feasibility of Counting Songbirds Using Unmanned Aerial Vehicles

    Full text link
    Obtaining unbiased survey data for vocal bird species is inherently challenging due to observer biases, habitat coverage biases, and logistical constraints. We propose that combining bioacoustic monitoring with unmanned aerial vehicle (UAV) technology could reduce some of these biases and allow bird surveys to be conducted in less accessible areas. We tested the feasibility of the UAV approach to songbird surveys using a low-cost quadcopter with a simple, lightweight recorder suspended 8 m below the vehicle. In a field experiment using playback of bird recordings, we found that small variations in UAV altitude (it hovered at 28, 48, and 68 m) didn\u27t have a significant effect on detections by the recorder attached to the UAV, and we found that the detection radius of our equipment was comparable with detection radii of standard point counts. We then field tested our equipment, comparing songbird detections from our UAV-mounted recorder with standard point-count data from 51 count stations. We found that the number of birds per point on UAV counts was comparable with standard counts for most species, but there were significant underestimates for some—specifically, issues of song masking for a species with a low-frequency song, the Mourning Dove (Zenaida macroura); and underestimation of the abundance of a species that was found in very high densities, the Gray Catbird (Dumetella carolinensis). Species richness was lower on UAV counts (mean = 5.6 species point−1) than on standard counts (8.3 species point−1), but only slightly lower than on standard counts if nonaudible detections are omitted (6.5 species point−1). Excessive UAV noise is a major hurdle to using UAVs for bioacoustic monitoring, but we are optimistic that technological innovations to reduce motor and rotor noise will significantly reduce this issue. We conclude that UAV-based bioacoustic monitoring holds great promise, and we urge other researchers to consider further experimentation to refine techniques
    corecore