Swarm UAV Communication Networks

Dual-mode radar and communications devices for use in swarms of autonomous drones. The devices combine radar sensing and high-speed data communication capabilities in a single module with low size, weight, power, and cost. The modules leverage integrated circuits, phased arrays, and software defined radio techniques to provide radar sensing at medium range and data communication at high rates. This enables swarms of drones to autonomously navigate, inspect objects, and share sensor data using a mesh network with focused radar beams to reduce interference.

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Determining an optimal communication structure to link a set of delivery drones with a base station in a way that maximizes the number of drones that can stay connected during long distance delivery missions. The structure involves positioning a subset of relay drones at static locations along the delivery routes. This allows the relay drones to form communication regions that the delivery drones can access when they pass through. By strategically selecting the relay drone locations, it minimizes the number of unsupported delivery drones. This balances the tradeoff between the relay drone count and the maximum number of hops from a delivery drone to the base.

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Dynamic grouping of semi-autonomous drones to efficiently perform tasks like surveillance, delivery, mapping, etc. The drones can self-organize into teams based on capability matching to execute complex operations. A server determines tasks and assigns drones based on capabilities. Lead drones decompose tasks and create plans. Followers execute tasks. If a leader fails, another drone takes over. This allows flexible and scalable drone swarms without centralized control.

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This paper introduces an Unmanned Aerial Vehicle - enabled content management architecture that is suitable for critical access in communities of users are communication-isolated during diverse types disaster scenarios. The proposed leverages a hybrid network stationary anchor UAVs and mobile Micro-UAVs ubiquitous dissemination. equipped with both vertical lateral communication links, they serve local users, while the micro-ferrying extend coverage across increased mobility. focus on developing dissemination system dynamically learns optimal caching policies to maximize availability. core innovation adaptive framework based distributed Federated Multi-Armed Bandit learning. goal optimize UAV decisions geo-temporal popularity user demand variations. A Selective Caching Algorithm also introduced reduce redundant replication by incorporating inter-UAV information sharing. method strategically preserves uniqueness preferences amalgamating intelligence learning system. approach improves algorithm's ability adapt preferences. Functional verification performance evaluation confirm architect... Read More

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This study introduces a novel framework for dynamic reconnaissance operations using Unmanned Aerial Vehicle (UAV) swarms, designed to adapt in real time changes mission parameters and UAV availability. Unlike traditional models that assume static operational conditions, our approach distinguishes between two key categories of change: Type I, related modifications the swarm (e.g., vehicle loss or deployment), II, concerning adjustments configuration area responsibility. These are jointly addressed within unified optimization based on Ant Colony Optimization (ACO), allowing efficient trajectory planning rapid replanning during execution. As part framework, we propose Pheromone Matrix Initialization (PMI) technique accelerate convergence I scenarios by reusing heuristic information from prior optimizations. The effectiveness overall is validated through six realistic scenarios, demonstrating its ability maintain continuity with minimal delay respond efficiently complex sequential changes. Comparative analysis shows consistent superior performance over classical state-of-the-art methods,... Read More

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Optimizing communication in swarms of drones to enable efficient and reliable control of large numbers of drones. The optimization involves clustering the drones into groups with a master drone that communicates with a central server, and slave drones that relay messages from the master. This reduces the number of required communication channels compared to each drone directly connecting. Clustering also allows faster area coverage, obstacle avoidance, and resource sharing. If a master fails, another slave can be promoted. This enables robust swarm operation by minimizing communication breakdowns.

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Swarm-based unmanned aerial vehicle (UAV) systems offer enhanced spatial coverage, collaborative intelligence, and mission scalability for various applications, including environmental monitoring emergency response. However, their onboard computing capabilities are often constrained by stringent size, weight, power limitations, posing challenges real-time data processing autonomous decision-making. This paper proposes a comprehensive communication computation framework that integrates cloud-edge-end collaboration with cell-free massive multiple-input multiple-output (CF-mMIMO) technology to support scalable efficient offloading in UAV swarm networks. A lightweight task migration mechanism is developed dynamically allocate workloads between UAVs edge/cloud servers, while CF-mMIMO architecture designed ensure robust, low-latency connectivity under mobility interference. Furthermore, we implement hardware-in-the-loop experimental testbed nine validate the proposed through object detection tasks. Results demonstrate over 30% reduction significant improvements reliability latency, highlig... Read More

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Optimizing the topology and power allocation for large-scale drone swarm networks to improve capacity in the presence of interference. The method involves a two-step optimization procedure. First, given a fixed network topology, an interior point method is used to find the optimal power levels for each drone to maximize network capacity. Then, a network topology optimization is performed by simultaneously finding the best connections between drones and their power levels to further increase capacity subject to constraints. The method handles interference from jammers and internal drone interference by introducing redundant variables and converting non-convex constraints into easier forms.

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Method and system for reliable networking of unmanned aerial vehicles (UAVs) using adaptive multi-hop transmission to improve connectivity and stability. The method involves prioritizing transmission in the same link and then hopping to adjacent links when congestion exceeds 95%. This prevents disconnections from isolating UAVs. The system has multiple UAVs forming transmission packets with at least one link per UAV. Long-range links are repaired instead of adding nodes, while short-range links use multiple nodes to maintain distance.

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Self-organizing network for unmanned aerial vehicles (UAVs) that allows UAVs to communicate with each other and ground stations without relying on fixed infrastructure. The network uses satellite links and mesh networking to connect a command center, portable satellite station, UAV swarm, ground mobile base, and individual soldiers. The UAV swarm can operate autonomously with direct links between UAVs and ground stations. The satellite station provides connectivity to the UAV swarm when out of range of ground stations. The command center coordinates the network and has satellite links to the satellite station and ground stations. This allows UAVs to communicate with each other and ground stations without relying on fixed infrastructure.

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Constructing a dynamic network topology for swarms of unmanned aerial vehicles (UAVs) that adapts to changing network conditions. The network has two levels: a first level with fixed cluster heads formed by medium/large UAVs, and a second level with temporary cluster heads formed by small UAVs. The small UAVs communicate with the fixed cluster heads through their temporary cluster heads. This allows flexible network organization that can quickly adapt to node mobility and topology changes.

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Wireless perception system energy and information transmission method for UAV swarms that enables efficient and reliable wireless perception in large-scale swarms. The method involves jointly optimizing power allocation, beamforming, and time division to maximize the total throughput of sensors in the swarm while ensuring data throughput in the UAV swarm. The optimization is done using a golden section search algorithm to find the optimal values for power allocation, beamforming, and time division.

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Method and device for enabling fast and reliable communication between drones in a swarm without fixed infrastructure like cell towers. The method involves establishing a separate coordinate system for each drone using UWB positioning. Drones share their coordinates in real-time. They also determine the overall swarm coordinates. Drones use this swarm coordinate data along with the drone's own time slot to route messages efficiently through the swarm. The drones dynamically update routing tables. This allows rapid construction of a dynamic ad-hoc network without relying on base stations.

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Method for constructing a drone swarm relay network without relying on absolute positioning. The method involves having the drones determine their relative positions by measuring distances between them using received signal strength indicator (RSSI). This allows them to build the network by flying and hovering at specific positions without needing absolute positioning systems like GPS. The drones can also calculate connectivity between themselves using relative positioning for network optimization.

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An unmanned aerial vehicle (UAV) system enabling swarm flight through coordinated communication between multiple UAVs. The system employs 5G wireless communication technology to facilitate real-time data exchange between UAVs, enabling autonomous formation and coordinated flight operations. The system includes a UAV controller that manages the swarm flight operations, and a 5G network that provides reliable and low-latency communication between the UAVs and the controller. The system also includes a UAV traffic management (UTM) system that provides route planning and collision avoidance services for the swarm.

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Secure communication method and device for multi-hop ad hoc networks using drones to improve reliability and performance compared to ground-based networks. The method involves using drones as relay nodes to create a distributed network. Communication between the drones and a central command center is done over MESH links. The drones collect data, process it locally, and if needed, collaboratively calculate with nearby drones. If still unable to complete processing, it's sent to the command center for cloud computing. This allows distributed computing to overcome limitations of limited drone resources. The method leverages the mobility and coverage of drones to provide secure, flexible, and resilient networking in areas without fixed infrastructure.

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A routing method for cluster drone communication that enables efficient and reliable communication in large-scale mobile nodes. The method uses a hierarchical routing structure with weighted clustering, where cluster heads are selected based on energy, connectivity, mobility, and distance. Reactive routing lookups are performed between cluster heads, discarding duplicate packets from the same node. This approach improves network scalability and reduces packet loss in dynamic drone networks.

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Unmanned aerial vehicle (UAV) communication system that uses a mesh network to enable better UAV connectivity and improve battery life of controllers. The system has a mesh device that acts as a relay between controllers and UAVs. The mesh network allows UAVs, controllers, and mesh devices to communicate indirectly through the mesh. This provides flexibility, scalability, and redundancy for UAV operations. The mesh network can bypass obstacles, extend range, and avoid line-of-sight issues compared to direct controller-UAV links.

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Avoiding collisions in wireless communication systems with multiple modules in close proximity by shifting the timing of monitoring total transmission time. Each module monitors its own transmission time during a fixed interval, and a central control determines different start times for the intervals. This distributes the concentrated transmission periods between modules, preventing simultaneous transmissions from colliding.

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Cooperative multi-UAV clusters have been widely applied in complex mission scenarios due to their flexible task allocation and efficient real-time coordination capabilities. The Air Command Aircraft (ACA), as the core node within UAV cluster, is responsible for coordinating managing various tasks cluster. When ACA undergoes fault recovery, a handover operation required, during which must re-authenticate its identity with cluster re-establish secure communication. However, traditional, centralized authentication mechanisms face security risks such single points of failure man-in-the-middle attacks. In highly dynamic network environments, single-chain blockchain architectures also suffer from throughput bottlenecks, leading reduced efficiency increased latency. To address these challenges, this paper proposes mathematically structured dual-chain framework that utilizes distributed ledger decouple management information. We formalize process using cryptographic primitives accumulator functions validate through BAN logic. Furthermore, we conduct quantitative analyses key performance metr... Read More

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