An approach for determining an infrastructure service interruption is disclosed. The approach relies on utilizing UAVs (unmanned aerial vehicle) to map electronic signals (e.g., Wi-Fi, etc.) that emanates from building structures (e.g., residential, commercial, etc.). Electronic signals having a certain frequency or multiple frequencies may be used. Essentially, the approach can detect power/signal loss by comparing differences in Wi-Fi signal maps pre and post event (e.g., severe thunderstorm, etc.). The 24/7 event monitoring is carried out by using UAVs and the UAVs can operate on a regular or event driven schedule vs. continuously operating multiple fixed data collection units.

An airborne RF-head platform system and method. Here, much of the computational burden of transmitting and receiving wireless RF waveforms is shifted from the airborne platform to a ground baseband unit (BBU). The airborne platform, which will often be a high altitude balloon or drone type platform, generally comprises one or more remote radio heads, configured with antennas, A/D and D/A converters, frequency converters, RF amplifiers, and the like. The airborne platform communicates with the ground baseband units either directly via a laser communications link, or indirectly through another airborne relay platform. The airborne RF-head communicates via various wireless protocols to various user equipment such as smartphones by using the BBU and the laser communications link to precisely control the function of the airborne A/D and D/A converters and antennas. This system reduces the power needs, weight, and cost of the airborne platform, and also improves operational flexibility.

In order for a mobile terminal to land at an appropriate landing point in reaction to a change of an incident that may occur while the mobile terminal flies along a flight path, a control apparatus 100 includes: an information acquisition section 131 configured to acquire, according to a flight of a first mobile terminal (mobile terminal 200a) performed based on a flight path to a first landing point, information on one or more second landing points associated with the flight path to the first landing point; and a first communication processing section 133 configured to transmit the information on the one or more second landing points to the first mobile terminal (mobile terminal 200a) via a mobile communication network 300.

An airborne RF-head platform system and method. Here, much of the computational burden of transmitting and receiving wireless RF waveforms is shifted from the airborne platform to a ground baseband unit (BBU). The airborne platform, which will often be a high altitude balloon or drone type platform, generally comprises one or more remote radio heads, configured with antennas, A/D and D/A converters, frequency converters, RF amplifiers, and the like. The airborne platform communicates with the ground baseband units either directly via a laser communications link, or indirectly through another airborne relay platform. The airborne RF-head communicates via various wireless protocols to various user equipment such as smartphones by using the BBU and the laser communications link to precisely control the function of the airborne A/D and D/A converters and antennas. This system reduces the power needs, weight, and cost of the airborne platform, and also improves operational flexibility.

Methods are provided for enabling network operators to play a key role in allowing Cellular Unmanned Aerial Vehicles (UAVs) to recharge batteries based on RF parameters and/or a class of service the UAVs provide to users/customers. For example, a particular mobile network operator (MNO) has a UAV charging station deployed in it leased towers where it has base stations (eNB/gNB) deployed. The MNO can provide charging as a service to the UAVs. When more than one drone is requesting a charge, the MNO can prioritize which UAV has the highest priority. In some aspects, the MNO can prioritize the UAVs for charging based on a Quality of Service identifier. Additionally or alternatively, the MNO can prioritize the UAVs for charging based on a Network Slice Selection Assistance Information indicator.

Methods, systems, and devices for wireless communications are described. In a wireless communications system, a base station may transmit an indication of a pre-compensation timing value for transmission of a random access message by an aerial user equipment (UE), the random access message part of a random access procedure between the base station and the aerial UE when the aerial UE is in a connected state. The pre-compensation timing value may be based on a location of the aerial UE. In some examples, the base station may monitor a set of random access resources associated with the pre-compensation timing value and the aerial UE for the random access message, and the aerial UE may transmit the random access message using a first random access resource of a set of random access resources associated with the pre-compensation timing value and the aerial UE.

Provided is a smart surveillance system that includes one unmanned aerial vehicle (UAV), a plurality of Internet of Things (IoT) terminals distributed in a surveillance area, and a plurality of base stations distributed in the surveillance area, wherein the UAV selects any IoT terminal from among the plurality of IoT terminals using deep learning auction training, receives surveillance data from the selected IoT terminal, and transmits the surveillance data to a data center through the Internet and any one base station among the plurality of base stations.

Methods, systems, and devices for wireless communications are described. In a wireless communications system, a base station may transmit an indication of a pre-compensation timing value for transmission of a random access message by an aerial user equipment (UE), the random access message part of a random access procedure between the base station and the aerial UE when the aerial UE is in a connected state. The pre-compensation timing value may be based on a location of the aerial UE. In some examples, the base station may monitor a set of random access resources associated with the pre-compensation timing value and the aerial UE for the random access message, and the aerial UE may transmit the random access message using a first random access resource of a set of random access resources associated with the pre-compensation timing value and the aerial UE.

The technology relates to managing nighttime power for solar-powered vehicles. A system may include a sunrise estimator for estimating a time until a next sunrise, a battery state estimator for estimating a battery state, a critical battery estimator for determining a battery threshold, below which subsystems may be powered off, and an alert monitor to determine, and communicate to the solar-powered vehicle, a charge threshold and a restart charge threshold. A method may include operating a vehicle in an operational power mode, estimating a time until a next sunrise, estimating a battery state, determining a preservation battery threshold based on the estimated time until the next sunrise and the estimated battery state, determining a minimum charge threshold based on the preservation battery threshold, monitoring a battery charge level of the vehicle throughout the night, and if the battery charge level drops below the minimum charge threshold, implementing a preservation power mode.

Methods are provided for enabling network operators to play a key role in allowing Cellular Unmanned Aerial Vehicles (UAVs) to recharge batteries based on RF parameters and/or a class of service the UAVs provide to users/customers. For example, a particular mobile network operator (MNO) has a UAV charging station deployed in it leased towers where it has base stations (eNB/gNB) deployed. The MNO can provide charging as a service to the UAVs. When more than one drone is requesting a charge, the MNO can prioritize which UAV has the highest priority. In some aspects, the MNO can prioritize the UAVs for charging based on a Quality of Service identifier. Additionally or alternatively, the MNO can prioritize the UAVs for charging based on a Network Slice Selection Assistance Information indicator.