Power Management for Drone Communication Systems

Optimizing wireless communications for unmanned aerial vehicles (UAVs) by dynamically selecting the carrier frequency based on network conditions and UAV operations. The method involves retrieving network state information describing the network conditions, determining the impact of those conditions on the UAV's operation, and then selecting an appropriate carrier frequency for UAV-network communications based on that impact. Factors like altitude, location, bandwidth availability, and future flight paths are considered.

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A method for optimizing federated learning performance and resource allocation using unmanned aerial vehicles (UAVs). The method determines optimal UAV positions, user resource allocation, and learning parameters to balance energy consumption and learning performance. It models the problem as an optimization problem that minimizes a total cost function representing energy consumption and learning performance, and solves it to obtain optimal UAV positions, user resource allocation, and learning parameters.

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Uplink/downlink resource allocation, beam adjustment, and power control for unmanned aerial vehicle (UAV) communication, enabling efficient resource management in high-flying, high-speed environments. The system establishes a mapping relationship between three-dimensional spatial regions and resources, allowing base stations to dynamically allocate resources based on UAV location and channel conditions. The mapping relationship is initially established through prior knowledge of resource allocation patterns, enabling real-time resource determination for UAVs. The system also implements optimized uplink power control parameters, enabling faster and more effective power adjustment in UAV communication systems.

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Access barring check based on height in wireless communication systems to efficiently perform load balancing in cellular networks by restricting access attempts for UEs above a certain height. The network configures access barring based on height ranges. The UE determines the applicable barring configuration based on its current location and performs the access check accordingly. This allows selective access control for aerial UEs like drones to reduce waste of resources at higher altitudes.

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Dynamic Quality of Service (QoS) management for communication between unmanned aerial vehicles (UAVs) and ground control stations (GCS) through a unified network architecture. The system enables efficient QoS provisioning across different communication paths (uplink and downlink) between UAVs and GCSs, ensuring optimal performance across varying network conditions. The QoS management is achieved through a group-based approach that dynamically adapts to communication requirements between UAVs and GCSs, enabling seamless QoS management across different communication paths.

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Wireless communication method for unmanned aerial vehicles (UAVs) that enables grouping information exchange between wireless communication nodes. The method includes transmitting UAV grouping information, such as group identifiers or authorized information, between nodes, and receiving UAV-related information, including identifiers, differentiation data, and flight parameters. The method enables coordination of multiple UAVs in a wireless network, facilitating applications like relaying and monitoring.

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Efficient resource allocation and uplink power control for unmanned aerial vehicle (UAV) communication systems. The system enables real-time mapping of UAV spatial locations to resources through pre-established channel quality relationships, allowing base stations to dynamically allocate resources based on the UAV's current spatial context. This mapping enables efficient resource allocation and real-time optimization of uplink power levels, particularly in high-flying UAVs with variable channel conditions.

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A communication device for aerial use, such as a drone, that reduces uplink inter-cell interference by dynamically controlling transmission power based on altitude and interference information received from neighboring cells. The device also enables flexible beamforming and virtual cell management to further improve communication quality and stability in aerial environments.

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Techniques for managing interference caused by unmanned aerial vehicles (UAVs) communicating with cellular networks. The UAVs actively reduce transmission power when communicating with cell towers to avoid interference with ground-based devices.

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Ensuring Quality of Service (QoS) for communication between unmanned aerial vehicles (UAVs) and their ground controllers through a unified network architecture. The system dynamically adapts QoS parameters based on the specific communication requirements between UAVs and ground stations, enabling optimized performance across different communication modes (direct, network-assisted, and UTM-navigated). The architecture achieves this through a unified group-based QoS provisioning approach that automatically adjusts parameters based on the specific communication scenario.

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A wireless perception system energy and information transmission method for a UAV swarm, enabling autonomous coordination of multiple UAVs to supply power and transmit data to a network of wireless sensors. The method employs a multi-AP architecture, where each UAV serves as an energy transmitter and data receiver for a subset of sensors, and optimizes transmission power, beamforming weights, and time division factors to balance energy harvesting and data throughput across the swarm.

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Optimizing UAV data acquisition systems through coordinated flight trajectory, wake-up scheduling, and time slot management to achieve maximum energy efficiency. The method iteratively optimizes these parameters through a combination of sub-problems, ensuring that both the transmission data amount and energy consumption of sensors are optimized while maintaining system performance.

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A system and method for controlling Quality of Service (QoS) in wireless links using multiple relay stations, including mobile stations such as drones. The system continuously monitors QoS metrics across the link and identifies hops where target values are not being met. It then determines and executes corrective actions to improve QoS, including adding mobile relay stations as needed to maintain sufficient quality.

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Real-time switching of power sources in unmanned aerial vehicles (UAVs) based on load profiles to optimize performance and battery life. The system monitors flight phases and commands to proactively switch between lithium polymer (LiPo) and lithium ion (Li-Ion) batteries in real time as the load profile changes. This allows using the appropriate battery type for the current load conditions to maximize efficiency and avoid battery degradation.

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Powering unmanned aerial vehicles (UAVs) through a novel battery management system that optimizes energy harvesting and storage during solar-powered flight. The system enables the UAV to ascend to higher altitudes during daylight hours by utilizing excess energy generated by the solar array, while maintaining optimal battery temperature limits. This approach enables the UAV to conserve energy during nighttime operations by descending to lower altitudes after sunset, thereby extending its flight duration and reducing overall mission duration. The system incorporates a power management system that dynamically controls charging and discharging of the battery pack based on solar array output and flight conditions.

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Enabling QoS management for UAV-Controller communication through a unified approach that integrates multiple network technologies. The system provisions QoS parameters for direct UAV-Controller communication, enabling both UAV originated and terminated QoS configurations. The provisioning is achieved through a group-based approach that recognizes UAV-Controller pairs based on their unique identifiers, allowing for centralized management of QoS parameters across both UAV and controller. The system enables adaptive QoS adaptation when communication conditions fail, ensuring consistent network resource allocation for both UAV and controller operations.

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Flying device that reduces transmission delays between the device and a control device by dynamically prioritizing data transmission based on communication quality and device attributes. The device determines communication quality and predicts flight trajectory to optimize data transmission, prioritizing flight control data over image data when communication quality is poor. The control device also prioritizes flight control data over other traffic when transmitting through a public network.

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Method for cell reselection in UAVs that avoids frequent cell reselection and improves stability while reducing power consumption by dynamically adjust the reselection parameters based on altitude. The base station sends the UAV a measurement parameter adjustment rule including altitudes and corresponding offsets/factors. The UAV adjusts its reselection parameters based on its current altitude using the rule. This avoids constant reselection as altitude changes, improving stability.

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Wireless communication system for unmanned aerial vehicles (UAVs) that optimizes resource allocation, beam adjustment, and power control through a mapping-based approach. The system establishes a mapping relationship between three-dimensional spatial regions and resources, where the base station allocates resources based on the mapping. The mapping is determined based on channel quality measurements and spatial location information, enabling real-time resource allocation and measurement. The system also provides fine-grained uplink power control parameters, enabling faster power adjustments compared to conventional configurations. This mapping-based approach enables efficient resource management for UAVs operating in environments with varying channel conditions.

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Direct command and control communication between a UAV and a controller through a unified network architecture, enabling optimized QoS management for both uplink and downlink communications. The system leverages a group-based approach to manage QoS across both the UAV and controller, with separate groups for uplink and downlink communications. A centralized network resource manager coordinates QoS provisioning and adaptation based on group identifiers, ensuring consistent QoS levels across both communication paths. This unified approach enables efficient QoS management while maintaining separate control interfaces for the UAV and controller.

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Optimizing the movement of multiple UAVs to efficiently provide wireless coverage with energy conservation. It uses a deep learning model called DDPG to continuously control UAV movements based on real-time observations. The model generates continuous control signals instead of discrete ones like Q-learning. The observations include UAV energy, user coverage, and fairness. The model learns from sampled mappings between observations and control signals. This allows more precise and fluid UAV movement control compared to discrete methods.

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Method for cellular networks to automatically detect when a drone-coupled wireless device like a UAV drone takes off and apply specialized protocols to optimize its connection. When a drone takes off, it triggers a session connectivity request to the network that includes an identifier for the aerial session. The network establishes a dedicated bearer with the drone and applies aerial-specific protocols for things like power control, handover, antenna config, etc. This allows the drone to maintain optimized connectivity while flying without interfering with ground users.

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A method for uplink power control in a cellular network for aerial User Equipments (UEs) that adapts transmit power based on the UE's flying status. The method involves receiving reference altitude information from the base station, detecting the UE's height above a threshold, and triggering a measurement report to the base station. The base station then sends an indication to use a specific fractional path loss compensation factor for uplink power control based on the UE's flying status. The UE performs uplink power control tasks using the selected compensation factor.

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Antenna system for communicating with networks from altitude changing objects, particularly drones, that dynamically optimizes transmit power based on altitude, location, and object orientation. The system determines optimal transmit power levels for each antenna based on real-time network parameters, such as cell coverage, interference patterns, and object motion. This enables precise power control to maintain network performance while mitigating interference from the drone's increased signal range.

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A system and method for controlling Quality of Service (QoS) in wireless links using multiple relay stations, including mobile stations like drones. The system continuously monitors QoS metrics and determines when target values are not being met. It then identifies and executes corrective actions to maintain QoS, including adding mobile relay stations as needed to ensure reliable communication.

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Wireless communication system enabling status reporting for airborne devices. The system includes a wireless device that reports its flight status to the network using a two-bit field with four distinct states, each corresponding to a predefined status. The network receives the status indication and configures the device accordingly, including power control, radio resource allocation, and handover management. The system also enables the network to detect and mitigate interference caused by airborne devices, and to optimize network performance based on the device's flight status.

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Optimizing UAV communication through dynamic height-based resource allocation. The system dynamically adjusts UAV operation parameters based on flight height, enabling more efficient resource utilization and interference management in UAV networks. The system continuously monitors UAV height and transmits height-related data to the base station, which uses this information to configure UAV operation parameters and resource allocation. This adaptive approach ensures optimal performance in UAV networks by dynamically adjusting parameters based on flight conditions, enabling better resource utilization and interference management.

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Optimizing resource allocation in UAV communications through dynamic height-based scheduling. The system dynamically adjusts resource allocation based on the UAV's height and a predefined height threshold, enabling more efficient use of available resources while minimizing interference. The system continuously monitors UAV height and adjusts resource allocation in real-time to maintain optimal communication performance.

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A power control method for aerial vehicles in wireless communication systems, particularly for unmanned aerial vehicles (UAVs) operating at varying altitudes. The method employs open-loop power control based on estimated path loss from neighboring cells, with the power control factor adjusted according to the UAV's altitude. The method enables UAVs to coexist with terrestrial users while minimizing interference, and can be implemented using reference signals and dynamic blanking of cell-specific reference signals.

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A system for aircraft monitoring that enables real-time data collection during flight phases while minimizing power consumption. The system comprises a sensor, a radio module conforming to a low-power wide area network standard, and a power management module with energy storage. The radio module transmits data to a radio access point, where it determines transmission power based on the aircraft's power state. The system implements adaptive transmission power management to optimize power consumption while maintaining data transmission capabilities.

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Method for operating a wireless interface between ultra-low power nodes and backbone nodes in a network, where the ultra-low power nodes transmit packets on multiple channels and the backbone nodes dynamically allocate which channels to listen on based on reception performance, enabling coordinated channel allocation across multiple backbone nodes.

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Method and apparatus for controlling transmit power in an unmanned aerial vehicle (UAV) control system to increase communication link availability and minimize interference with other links. The system determines the required transmit power based on the signal-to-noise ratio (SNR) margin and the maximum allowed transmit power, and adjusts the transmit power accordingly. The system also considers propagation delay and fading channel characteristics to ensure accurate power control.

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