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Flying Ad Hoc Network (FANET) is a novel mobile ad hoc network type where the communicating nodes are Unmanned Aerial Vehicles (UAVs). Deployment of traditional omnidirectional antennas on FANETs lacks to address enhanced spatial reuse demands because interference by simultaneous transmissions limits the maximum number of concurrent communications. Alternatively, utilization of directional antennas can significantly increase the spatial reuse and network capacity of FANETs. In this paper, we present an analytical study to specify the maximum number of active UAV node pairs for three dimensional (3D) flight scenarios. Specifically, we propose an analysis for various flight scenarios over different types of flights and present the effects of the distance between communicating nodes and the main beam angles on the number of maximum active node pairs.

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One of the most critical issues of Wireless Sensor Networks (WSNs) is the deployment of a limited number of sensors in order to achieve maximum coverage on a terrain. The optimal sensor deployment which enables one to minimize the consumed energy, communication time and manpower for the maintenance of the network has attracted interest with the increased number of studies conducted on the subject in the last decade. Most of the studies in the literature today are proposed for two dimensional (2D) surfaces; however, real world sensor deployments often arise on three dimensional (3D) environments. In this paper, a guided wavelet transform (WT) based deployment strategy (WTDS) for 3D terrains, in which the sensor movements are carried out within the mutation phase of the genetic algorithms (GAs) is proposed. The proposed algorithm aims to maximize the Quality of Coverage (QoC) of a WSN via deploying a limited number of sensors on a 3D surface by utilizing a probabilistic sensing model and the Bresenham's line of sight (LOS) algorithm. In addition, the method followed in this paper is novel to the literature and the performance of the proposed algorithm is compared with the Delaunay Triangulation (DT) method as well as a standard genetic algorithm based method and the results reveal that the proposed method is a more powerful and more successful method for sensor deployment on 3D terrains.