3D placements of drones in a millimeter-wave network to maximize the lifetime of wireless devices

Abstract

In the last few years, the use of drones is increasing day by day in wireless networks and the applications of them are rapidly increased on different sides. Now, we can use the drone as an aerial base station (BS) to support cellular networks in emergency cases and in natural disasters. To take the advantage of both drones and fifth-generation (5G) and link between their features, we study an aerial BS considering millimeter waves (mm-waves). In this paper, we optimize the 3D placements for multiple unmanned aerial vehicles (UAVs) in an mm-wave network to achieve maximum time durations of the uplink transmission. First, we present a formulation for the placement problem, where we aim to allocate 3D locations for multiple UAVs to achieve the maximum sum of time durations of uplink transmissions. We propose an efficient algorithm to find the placements of UAVs. We propose an algorithm that starts by grouping the wireless devices into a number of clusters, and each cluster is served by a single UAV. After the clustering process, it applies the gradient projection-based algorithm (GP) or particle swarm optimization (PSO) in each cluster. In the results section, our proposed approach and the center projection algorithm will be compared to prove the efficiency of our approach.

3D Placement Optimization in UAV-Enabled Communications: A Systematic Mapping Study

“…The ultimate goal is to have a UAV-based network operating continuously for an extended period. Only two contributions ( i.e., [77], [80]) focus on optimizing…”

“…To ensure that, several analyzed papers, including [65], [66], [91], [167], [182], use antennas with reconfigurable beamforming. Other papers, such as [80], [91], [163], [168], employ mmWave technology, known for its highly directive beam that facilitates clear communication between transmitters and receivers.…”

“…At 10% of the papers (i.e., [64], [68], [70], [76], [79], [80], [96], [98], [109], [122], [132], [168], [185]) have employed the OFDMA technique. For Example, articles like Ye et al [70] and Xu et al [76] focus on OFDMA to serve many ground users.…”

Efficient Data Collection in UAV‐Assisted Cluster‐Based Wireless Sensor Networks for 3D Environment: Optimization Study

“…They present two effective methods for reducing the number of UAVs required to serve wireless devices. In [23,24], the authors investigate the problem of efficient 3D placements for a set of UAVs in a mmWave network. The objective function of the optimization problem is aimed at finding the most effective UAV deployments that maximize the total uplink transmissions' time duration of ground wireless devices in a mmWave network.…”

“…(i) Constraint Equation (31a) ensures that the maximum transmit power for each CH should not exceed its maximum transmit power. It can be calculated from Equation ( 28 (vi) Constraint Equation (31f) is the maximum power constraint which ensures that the maximum transmit power for each CM should not exceed its maximum transmit power, and it can be calculated from Equation (23) (vii) Constraint Equation (31g) to Equation (31i) represent the minimum and maximum allowed values for the coordinates of the UAV Clustering sensor nodes is an efficient topology control strategy for reducing sensor node energy consumption and maximizing WSN lifetime. In a cluster-based WSN, the cluster heads face some additional burdens for operations like as data collecting, data aggregation, and data transfer to the base station.…”