Drone Frequency Allocation and Spectrum Management Solutions

Spectrum allocation optimization for covert transmission of multi-drone networks to improve spectrum utilization while ensuring confidentiality. The method involves maximizing drone-to-ground information transmission satisfaction subject to routing, bandwidth, power, block length, concealment, and SNR constraints. It transforms multi-drone routing into an alliance game, jointly optimizes routing, bandwidth, block length, and power using iterative coordinated descent and particle swarm optimization.

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Managing communication connections of unmanned aerial vehicles (UAVs) in a mobile network to enable reliable and efficient UAV operations while addressing challenges like ping-ponging, interference, and coverage. The method involves receiving UAV requirements, determining optimal radio frequency bands based on factors like flight path, weather, restrictions, and task needs, and sending a control signal to the UAV with the selected bands. This allows the UAV to use the specific bands during flight to improve performance, coverage, and reliability.

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Frequency band scheduling strategy for a multi-IRS-UAV assisted wireless power supply communication system that maximizes sum rate and reduces interference. The strategy involves dividing the spectrum into sub-bands, defining interference ranges for receivers, and iteratively selecting optimal bands for each device using successive fixation. This improves system quality by minimizing co-channel interference and reducing single-frequency interference risk.

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Intelligent spectrum sensing and anti-interference communication system for self-organizing network drones that enables adaptive frequency selection and dynamic spectrum access for drones operating in dynamic and interference-prone environments. The system uses onboard spectrum sensing to detect interference levels at candidate frequencies and dynamically select the best frequency point for communication based on interference. This allows drones to avoid strong interference frequencies and use complex modulation techniques to improve reliability in poor conditions. The system also periodically checks eliminated frequencies to restore them if interference clears.

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Maintaining network connectivity for unmanned aerial vehicles (UAVs) during flight to facilitate aerial navigation and operation. Flight routes and channel allocation instructions are generated based on flight plans and geographic information. This allows UAVs to connect to cellular networks at altitude without interference. The instructions can be adjusted during flight to mitigate issues like interference events. The coordinated airspace sharing and network distribution improves efficiency and safety of UAV operations.

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Optimizing RF spectrum allocation for air-to-ground communications in aviation networks to enable reliable and continuous communications for flights. The method involves generating RF coverage plans for flights based on submitted flight plans. The plans allocate specific spectrum resources at each location during the flight to avoid interference and ensure coverage. The system considers factors like geographic ranges, altitudes, and other flights. It can also optimize spectrum usage globally across multiple flights. This allows coordinated spectrum assignments for concurrent flights without degrading link quality.

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Improving wireless communication between drones and ground stations in congested RF environments by having the drones act as access points and isolating uplink traffic to a single resource unit while allowing wider resource units for downlink. This reduces interference and improves reliability compared to channel switching. The drone connects to the ground station using a wireless protocol that divides spectrum into resource units. The drone identifies a single resource unit for uplink and instructs the ground station to transmit there. This isolates uplink traffic and prevents interference from other devices. The downlink uses wider resource units.

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Optimizing communications between unmanned aerial vehicles (UAVs) and terrestrial networks by dynamically selecting carrier frequencies based on network state information and UAV operational constraints. This allows matching UAV connectivity needs with available network resources. The system retrieves network state data describing network conditions and UAV impacts, then selects frequencies to minimize impact on UAV operations. Factors considered can include altitude, location, network load, future requirements, current conditions, etc.

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Managing RF spectrum for air-to-ground communication in aviation to provide reliable and continuous links for unmanned drones and other aircraft. A flight plan-based system allocates dedicated spectrum channels to aircraft during flights. It determines available spectrum based on flight details, selects channels, and avoids interference. The system also dynamically configures links during flights to mitigate issues. This allows aircraft to have uninterrupted comms across multiple bases without contention.

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Method for allocating electromagnetic spectrum in swarm drone networks to efficiently utilize spectrum resources, reduce interference, and improve anti-jamming capability. The method involves three steps: frequency allocation, time distribution, and power control. Frequency allocation is hierarchical to save resources. Time division multiplexing is used to further reduce interference. Power control is non-cooperative to optimize performance. The method is based on game theory algorithms.

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Dynamic frequency allocation and management for unmanned aerial vehicles (UAVs) to increase spectrum utilization and allow multiple UAVs to share limited control frequencies. The method involves analyzing interference between channels and dynamically assigning and reusing frequencies in real time during UAV operation. This allows efficient frequency reuse and channel sharing compared to fixed assignments. After UAV operation, frequencies are recovered for other uses.

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A spectrum access method for unmanned aerial vehicles (UAVs) to efficiently allocate spectrum resources and improve throughput in dynamic wireless environments. The method uses a multi-user non-coupling queuing algorithm to balance channel selection, stability, and throughput. The UAVs make independent channel decisions based on queue sizes, interference power, and historical usage. This allows distributed UAV swarms to coordinate spectrum access without centralized control. The algorithm reduces frequency conflicts, improves channel utilization, and maintains stable queues compared to centralized or coupled methods.

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A cellular-based communication system for unmanned aerial vehicles (UAVs) and remotely piloted vehicles (RPVs) that enables reliable and high bandwidth communication for commercial applications while complying with airspace regulations. The system uses two separate RF frequency bands: one for payload data transmission between UAVs and ground stations, and another dedicated band for critical command and control datagrams between UAVs and airspace controllers. This allows separate communication channels for UAV functions like sensing vs navigation. It also provides elevated communication areas for UAVs to communicate via cellular-like networks above ground level. This allows UAVs to continue communicating with ground stations while operating in controlled airspace.

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System to enable reliable communication with unmanned aerial vehicles (UAVs) and remotely piloted vehicles (RPVs) operating at different altitudes. The system uses separate frequency bands for ground-level and aerial communications. It projects cellular network coverage into the sky to provide continuous communication for UAVs and RPVs at altitude. The ground-level band is for terrestrial devices. The aerial band is for aircraft using skyward-pointing antennas. Separation by frequency and polarization prevents interference. This allows reliable command/control at altitude without satellite dependence.

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Cognitive unmanned aerial vehicle (UAV) communication network design method using intelligent reflectors to improve network performance and spectrum efficiency. The method involves optimizing UAV position, phase shifts on intelligent reflectors, and sensing durations. It leverages cognitive radio to enable UAVs to sense primary network states and dynamically access them. This coordinated optimization of UAVs, reflectors, and spectrum sensing mitigates interference, reduces waste, and maximizes reachable rates.

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Authorization-free spectrum access method for unmanned aerial vehicles (UAVs) in a mobile edge computing (MEC) network using unlicensed spectrum. The method involves joint optimization of duty cycle, flight path, power allocation, and bandwidth assignment to maximize total capacity of UAV-based MEC. It allows UAVs to serve multiple user types with different requirements in hotspots using unlicensed spectrum. The optimization balances UAV mobility, spectrum sharing, and user rate guarantees.

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Spectrum sharing method for satellite-UAV hybrid networks that allows efficient sharing of spectrum between satellites and UAVs. The method involves optimizing UAV power allocation and hover times to balance UAV communication needs with satellite interference constraints. By maximizing UAV data transmission efficiency subject to constraints like UAV-satellite interference, UAV energy limits, and total UAV hover time, the method finds UAV power and hover schedules that enable coexistence with satellites sharing the same spectrum.

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Dynamic channel allocation method for unmanned aerial vehicles (UAVs) to efficiently use and manage limited spectrum for controlling UAVs in national airspace. It allows dynamically allocating and changing communication channels for UAVs as they fly between areas with different channel requirements. The method involves UAV ground control stations (GCS) requesting channels from the frequency authority before takeoff. During flight, if the UAV enters a new area requiring different channels, it requests a new set before entering. This avoids mid-flight channel changes. The authority checks channel availability. It balances static allocation vs dynamic requesting based on UAV density and spectrum needs.

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Method for efficiently operating multiple unmanned aerial vehicles (UAVs) in a limited frequency band dedicated to controlling UAVs in national airspace. The method involves dynamically allocating and managing the limited frequency resources for UAV control, allowing recovery and reuse of frequencies after operation. This supports efficient operation of multiple UAVs in a limited band versus fixed allocation. The method involves initial channel setup between ground station and UAV using manual or automatic methods.

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Efficiently using limited frequency resources for unmanned aerial vehicles (UAVs) by dynamically allocating additional frequencies for high-bandwidth missions. The method involves initially using a minimum frequency for takeoff/landing control. Then, when the UAV begins a mission requiring large data transfers, it allocates extra frequencies from ground control equipment dedicated to missions. This allows efficient frequency reuse and prevents saturation as the number of UAVs increases. The ground control equipment can swap roles between takeoff/landing and mission control to adaptively allocate resources based on UAV needs.

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