Latency Optimization in Multi-Hop UAV Networks

Aerial network architecture using hybrid communication links like FSO and RF that allows simultaneous transmission and failover protection. The network nodes like drones have overlay networks with FSO transmitters/receivers and RF transmitters/receivers. A processor modulates data for both links and balances traffic preemptively based on mission planning and link conditions. This reduces congestion and packet loss during link failures. The processor also uses packet erasure coding to recover from spurious FSO link loss without needing error prediction. The hybrid links and techniques provide resilient and efficient networking for aerial platforms.

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Joint optimization of UAV communication system components to maximize energy efficiency through intelligent reflecting surfaces. The method integrates active beamforming of the base station, passive beamforming of the intelligent reflecting surface, and trajectory optimization of the UAV to achieve maximum energy efficiency. The optimization process iteratively solves for optimal flight trajectories, beamforming parameters, and surface parameters, converging through the Dinkelbach algorithm. This approach enables the creation of high-performance wireless networks that balance signal transmission power with UAV mobility and surface deployment flexibility.

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Airborne short message communication method, apparatus, device, and system that dynamically adjusts message type and transmission frequency based on control commands to optimize communication efficiency and ensure timely transmission of critical information. The method selects a target message type from candidate types and determines transmission frequency based on the control command, then generates and transmits the message accordingly. This enables flexible communication management and emergency response capabilities.

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A method for controlling wireless communication between devices, particularly in high-mobility scenarios, involves allocating radiation boundary volumes to devices based on their positions. The method enables efficient resource allocation by dividing space into controlled radiation areas, which can be dynamically adjusted based on device movement. This approach optimizes communication performance in environments with multiple devices, such as vehicles and aerial systems, by intelligently managing radiation patterns and resource allocation.

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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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A system for optimizing data transmission in connected vehicles by programmatically customizing redundant data stream optimality criteria and automating clusterization of data streams according to similarity of projected optimal criteria. The system uses an orchestrator to control assignments of redundant data streams to wireless communication channels, optimizing based on an optimization model that enforces constraints such as channel diversity and latency. The model can be derived from simulation and trained using reinforcement learning, and can be updated in real-time to adapt to changing network conditions.

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A system and method for optimizing mission planning of a multi-UAV network for data collection and communication relay. The system includes a mission information definer, a data collection UAV mission planning optimizer, and a communication relay UAV mission planning optimizer. The method involves defining data collection mission information and parameters, optimizing mission planning of data collection UAVs, and optimizing mission planning of communication relay UAVs. The optimization process includes determining data collection orders, generating flight paths, and scheduling communication networks. The system enables autonomous mission planning for multi-UAV networks in environments with poor communication infrastructure.

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Joint optimization method for scheduling, trajectory, and power of a UAV relay system, which enables efficient communication in disaster scenarios by dynamically allocating resources among multiple UAVs to maximize throughput and minimize power consumption.

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Enhancing network resource management through coordinated coverage expansion in Unmanned Aerial Vehicles (UAVs) networks. The method involves a UAV node detecting when its resource utilization exceeds a threshold, then transmitting a resource assistance request to neighboring UAVs. The neighboring UAVs respond with confirmation of their willingness to provide assistance, and the UAV node adjusts its coverage area based on the assistance confirmation. This enables efficient resource sharing between UAVs while maintaining optimal network performance.

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A UAV-based computing system that enables direct communication between sensors and base stations through full-duplex relays. The system optimizes sensor placement, transmission power, and UAV flight paths to achieve reliable and efficient wireless communication. The optimization process iteratively solves sub-problems to find the optimal configuration that balances sensor coverage, transmission power, and UAV flight performance.

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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 wireless network architecture that separates control and data planes to optimize network performance in dynamic environments. The control plane uses a frequency-hopped control channel to manage network resources and disseminate network state information, while the data plane operates independently to forward packets based on up-to-date routing decisions. This separation enables high link-level robustness and unified routing with minimal communication overhead, particularly in environments with severe spectral and environmental degradations.

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Controlling swarms of unmanned aerial vehicles (UAVs) for applications like wireless communications where the UAVs act as relays. The UAVs coordinate their positions and behaviors to enhance network coverage and performance. The UAVs sense each other's locations and use that information along with network metrics to adapt their flight paths. This enables optimized UAV configurations for cooperative MIMO wireless communications. The UAVs also use swarm intelligence techniques like particle swarm optimization to autonomously coordinate their movements.

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Airborne short message communication method, apparatus, device, and system that dynamically adjusts message type and transmission frequency based on control commands to optimize communication efficiency and ensure timely transmission of critical messages. The method selects a target message type from candidate types and determines a transmission frequency based on the control command, then generates and transmits the message accordingly. This enables flexible communication management and emergency response capabilities.

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A method and device for orchestrating the execution of multiple mechanisms in a wireless network to achieve ultra-reliable and low-latency communication (URLLC) while maintaining efficiency. The method determines an initial mechanism orchestration strategy based on quality of service (QoS) targets, executes it, and then dynamically adjusts the strategy based on real-time latency data and network state classification. The device implements this method to optimize mechanism execution and resource allocation in real-time, enabling URLLC applications such as industrial automation, smart grids, and remote healthcare.

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Method for controlling a multi-hop transmission in a wireless communication network, comprising estimating an overall transmission delay of a data signal by a multi-hop transmission in a wireless communication network, said transmission being implemented by a system comprising a source equipment and a plurality relay equipment configured to receive, amplify and retransmit a radio signal emitted by the source equipment, and verifying that this overall transmission delay is less than or equal to a maximum authorized delay.

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Optimizing LTE communication for unmanned aerial vehicles (UAVs) by allocating time-frequency resources based on UAV height. The optimization involves determining height thresholds for UAVs, configuring operation modes based on height, and performing resource allocation based on height. This allows customized resource optimization for UAVs with varying flight heights.

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Configuring UAV operation based on height thresholds to optimize communication performance. The configuration enables dynamic height-based resource allocation and interference management for UAVs operating in cellular networks, particularly when their flight heights exceed typical coverage boundaries. The configuration system generates height-related information and communicates it to base stations to dynamically configure UAV operation modes and resource allocations, ensuring optimal performance in both coverage and interference scenarios.

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Enhancing UAV communication through dynamic height threshold management in LTE networks. The system dynamically adjusts height thresholds for UAVs based on their flight characteristics, cell coverage, and base station configuration. This enables optimized resource allocation and interference management in UAV communication scenarios, particularly when the UAV's height exceeds typical ground-level boundaries. The system continuously monitors UAV flight conditions and adjusts height thresholds in real-time to maintain optimal communication performance.

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Self-organizing, autonomous network of unmanned aerial vehicles (UAVs) that can provide high-bandwidth wireless backhaul connectivity over long distances beyond line-of-sight. The network uses a high bandwidth mmWave wireless mesh backhaul between the UAVs to enable applications like LTE coverage in disaster areas, wide-area search and rescue, and autonomous surveillance in inaccessible areas. The UAVs jointly optimize position, yaw, and traffic routing to efficiently configure the network. A migration process determines the optimal configuration in the least time to reconfigure the network dynamically in response to events.

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