Provided is a system including: a management unit configured to manage a plurality of battery packs connected in parallel, in which the management unit is configured to control the plurality of battery packs to cause the plurality of battery packs to be discharged alternately so that a discharge rate of each of the plurality of battery packs becomes higher than the discharge rate in a case of discharging all of the plurality of battery packs. The plurality of battery packs include a plurality of left-hand side battery packs and a plurality of right-hand side battery packs, and the management unit is configured to manage the plurality of battery packs to cause at least one of the plurality of battery packs in each of the plurality of left-hand side battery packs and the plurality of right-hand side battery packs to be discharged at a time in order.

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.

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.

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.

A drone system is configured to capture an audio stream that includes voice commands from an operator, to process the audio stream for identification of the voice commands, and to perform operations based on the identified voice commands. The drone system can identify a particular voice stream in the audio stream as an operator voice, and perform the command recognition with respect to the operator voice to the exclusion of other voice streams present in the audio stream. The drone can include a directional camera that is automatically and continuously focused on the operator to capture a video stream usable in disambiguation of different voice streams captured by the drone.

Provided are a network selection method and an apparatus for integrated cellular and drone-cell networks, where the method includes: acquiring a dynamic network model and a dynamic user model, generating a random event vector according to the dynamic network model and the dynamic user model; generating an action vector according to the random event vector; obtaining an individual utility of each user according to the action vector and the random event vector; constructing a first selection model; obtaining the value of the action probability according the first selection model to determine networks that the users choose to access according to the value of the action probability.