Signal Steering and Beamforming for Drone Communications

Sector sweep method for beam training in wireless communication systems like 6G that improves efficiency by using a short training sequence instead of a long frame. The method involves a first device transmitting a frame with info about multiple training sequences to a second device. They both perform beam training on a secondary frequency using those sequences instead of full frames. This allows faster and more accurate beamforming compared to traditional sector sweep methods.

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Edge device for accelerating user equipment (UE) specific beamforming using onboard sensing, tracking, and beamforming functions for reliable and high performance mmWave communications. The device has a sensor that detects and tracks users in its surrounding area. It then uses the sensor data to dynamically steer beams from its antenna array directly at the tracked users, even as they move, without relying on network signaling. This enables faster and accurate beamforming decisions for consistent high throughput and reliability compared to wide beam access. It reduces infrastructure needs by concentrating radiation patterns.

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Extending wireless coverage in hard-to-reach areas using drones with reconfigurable intelligent surfaces (RIS) to steer radio signals. The drones have panels with RIS that can reflect signals in specific directions. Flexures connect the panels to the drones to hold them in orientations that steer the reflected signals. This allows expanding coverage to remote or obstructed locations by deploying drones with RIS. The RIS orientation can be changed by activating flexures to steer the reflected signal to different targets.

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Thermal diffusion device for effectively dissipating heat in compact electronic devices. The device has a wick, working fluid, and support bodies inside a housing. The wick has through-holes and protrusions that contact the support bodies. This configuration reduces the area of wick blocking fluid flow. By closing off part of the wick near the support body, it allows more fluid flow and heat transport through the wick. The protrusions also provide contact for better wick-support adhesion. The device can be used in compact devices like smartphones to efficiently dissipate high heat loads.

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Accelerating user equipment (UE) specific beamforming for high performance and reliable communication using a dual function edge device that combines edge computing with beamforming capabilities. The edge device senses the surrounding area, generates a 3D map, recognizes UEs in motion, tracks their positions, and dynamically steers beams to those UEs based on the map and tracking. This enables faster and more reliable beamforming for UEs as they move, overcoming issues like signal attenuation and coarse positioning.

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Display integrated with antennas for improved communication quality and reduced device size. The display has pixels with light-emitting regions and shielded regions. Antenna elements are placed in the shielded regions. This allows the antennas to be above the display without interference. It also saves space by not needing external antennas. The display can have multiple integrated antennas for MIMO communication. A radio front-end circuit is shared between the pixels and antennas. The display thickness is reduced by sharing the circuit layer. The antennas can be controlled individually for beamforming.

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Circuits for precisely trimming the magnitude and phase of RF signals in radio frequency (RF) communication systems, such as millimeter-wave systems, to improve beamforming accuracy. The circuits use digitally-controlled transistors to selectively connect impedance elements like resistors and capacitors onto the signal path between input and output terminals. This allows fine-grained adjustment of magnitude and phase without bulk or power penalties compared to traditional approaches. The circuits can compensate for systematic and random offsets in RF chains to improve beamforming accuracy for applications like mmWave communications.

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Scalable and universal beamforming optimization using deep learning for wireless communication systems with arbitrary numbers of antennas and users. The technique involves a bipartite graph neural network (BGNN) that can adapt to any antenna and user configuration without retraining. The BGNN has three types of reusable component DNNs to process antenna and user vertices. It reduces dimensionality of the beamforming solution without loss by iteratively passing messages between vertices using weighted channel fading coefficients. This allows beamforming optimization for any network size. The BGNN can be trained on random bipartite graphs to further improve universality.

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Coexistence of unlicensed wireless devices with licensed spectrum users in the same frequency band. The unlicensed devices use techniques like puncturing, power reduction, and beamforming to avoid interfering with licensed entities. They obtain spectrum usage data from a database to identify licensed users in their area. For puncturing, they disable transmissions on sub-bands used by licensed users and instead use adjacent channels. For power reduction, they lower output to reduce interference on licensed sub-bands. For beamforming, they steer transmissions away from licensed sources to reduce interference.

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Compact, thin, and lightweight simultaneous beamforming module for wireless communication in applications like remote sensing CubeSats and UAVs. The module enables simultaneous transmission and reception of signals at two close frequency bands without using digital phase shifters or bulky air gaps between beamformers. It uses stacked dual-band analog beamformers with common ground planes and filters to pack beamforming elements closely together. This allows a compact module that can fit on small platforms.

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Beamforming for unmanned aerial vehicles (UAVs) that uses the UAV's and remote station's locations and the UAV's rotation to determine the beamforming direction without channel characterization. The UAV determines the direction based on its own location, rotation, and the remote station's location. It then beams data to that direction without channel feedback or training. This allows dynamic beamforming without the overhead and complexity of frequent channel characterization as the UAV moves.

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In this paper, we investigate a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted non-orthogonal multiple access (NOMA) communication system where the STAR-RIS is mounted on an unmanned aerial vehicle (UAV) with adjustable altitude. Due to severe blockages in urban environments, direct links from base station (BS) users are assumed unavailable, signal transmission realized via STAR-RIS. We formulate joint optimization problem that maximizes sum rate by jointly optimizing UAVs altitude, BS beamforming vectors, phase shifts, while considering Rician fading channels altitude-dependent factors. To tackle maximum achievable problem, adopt block-wise framework employ semidefinite relaxation gradient descent methods. Simulation results show proposed scheme achieves up 22% improvement significant reduction bit error (BER) compared benchmark schemes, demonstrating its effectiveness integrating UAV NOMA networks.

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Multi-Beam frequency scanning leaky-wave antennas (FBS-LWAs) offer a viable solution for hardware miniaturization in direction-of-arrival (DOA) estimation systems. However, the presence of multiple spatial harmonics results responses directions given incident source, introducing ambiguity and significantly challenging accurate DOA estimation. Moreover, due to nonlinear response FBS-LWA, its matrix does not satisfy Vandermonde structure, which renders common rank-recovery techniques ineffective processing coherent signals. As result, sources using multi-beam FBS-LWAs remains an open problem. To address this issue, paper proposes novel method signals based on antennas. First, received are transformed into domain via fast Fourier transform (FFT) construct signal data from covariance is computed.Then, conventional beamforming (CBF) employed obtain initial estimate angle set, will be further refined by smaller grid form candidate set. Finally, maximum likelihood algorithm stochastic principle (Sto-ML) used suppress interference parasitic select final estimates Simulation show that propose... Read More

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The development of beyond 5G (B5G) future wireless communication networks (FWCN) needs novel solutions to support high-speed, reliable, and low-latency communication. Unmanned aerial vehicles (UAVs) reconfigurable intelligent surfaces (RISs) are promising techniques that can enhance connectivity in urban environments where tall buildings block line-of-sight (LoS) links. However, existing UAV-assisted strategies do not fully address key challenges like mobility management, handover failures (HOFs), path disorders dense environments. This paper introduces a deep deterministic policy gradient (DDPG)-based UAV-RIS framework overcome these limitations. proposed jointly optimizes UAV trajectories RIS phase shifts improve throughput, energy efficiency (EE), LoS probability while reducing outage (OP) HOF. A modified K-means clustering algorithm is used efficiently partition the ground users (GUs) considering newly added GUs as well. DDPG algorithm, based on reinforcement learning (RL), adapts positioning configurations continuous action space. Simulation results show approach significantly r... Read More

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This article considers a multi-cell wireless network comprising of conventional user equipment (UE), sensor devices and unmanned aerial vehicles (UAVs) or drones. UAVs are used to assist base station, e.g., improve coverage collect data from devices. The problem at hand is optimize the (i) sub-carrier assigned cell (ii) position each UAV, (iii) transmit power following nodes: stations UAVs. We outline two-stage approach maximize fairness-aware sum-rate UE In first stage, genetic algorithm (GA)-based assign sub-band all cells determine location UAV. Then, in second linear program results demonstrate that our proposed achieves approximately 97.43% optimal obtained via brute-force search. It also attains on average 98.78% performance computationally intensive benchmark requires over 478% longer run-time. Furthermore, it outperforms GA-based allocation heuristic by 221.39%.

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In this paper, we study an unmanned aerial vehicle (UAV)-enabled maritime communication system, where a single rotary-wing UAV is dispatched to communicate with multiple moving vessel users. We formulate the energy efficiency optimization problem propulsion consumption model by jointly considering transmit power, flight trajectory, and velocity. The non-convex fractional programming problem, which makes it difficult obtain optimal solution. To solve propose efficient algorithm utilizing successive convex approximation techniques Dinkelbach (SCAD) algorithm. particular, divide original into three involved sub-problems that can be solved adopting alternate optimization. order satisfy constraint of maximum velocity, modified trajectory matching positions. Numerical results demonstrate effectiveness proposed scheme effectively improves for communication. Meanwhile, SCAD shows outstanding performance in terms long-duration flight.

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Wideband extremely large array antenna system and an OFDM-based hybrid beamforming method for improving data rate by maximizing signal strength in wideband MIMO systems with a large number of antennas. The method involves separate analog and baseband beamforming steps. The analog beamforming is designed using oblique projection matrices to decompose the hybrid field into orthogonal near-field and far-field components. A common analog beamforming matrix is then extracted by finding dominant eigenvectors from the decomposed matrices. Baseband beamforming is done separately for each subcarrier to maximize data rate on the effective channels.

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Abstract The present work investigates hierarchical beamforming strategies for millimeterwave communication systems, focusing on amplitude tapering and subarray approaches. research addresses key challenges in Angle of Arrival (AoA) estimation beam management, essential nextgeneration wireless networks. taperingbased method, implemented a 4element linear array, demonstrated precise beamwidth sidelobe control, enabling search with reduced implementation effort. Experimental validation confirmed its effectiveness identifying transmission directions under lineofsight conditions; however, reliance fullarray activation made it less energyefficient more sensitive to multipathinduced errors reflective environments. Conversely, the approach, applied an 8element showcased enhanced robustness against multipath effects quantifiable power savings. By activating only subset elements at each level, this method achieved estimated 42% reduction average per configuration significantly fewer evaluations than exhaustive search. Its adaptability supported efficient AoA b... Read More

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ABSTRACT Fifthgeneration (5G) and beyond communication systems, supported by Intelligent Reflecting Surfaces (IRS), frequently face challenges like less reliable communication, increased energy consumption, high latency. Passive beamforming at the reflecting surfaces is essential to enhance received signal quality, coverage, overall performance of system. Implementing passive in IRSaided systems poses vehicular environments, particularly with roadside IRS units fastmoving users. This paper proposes an efficient moderately lowcomplexity algorithm for highvelocity using mmWave networks. The optimizes reflection coefficients proposed Successive Convex Approximation based Interior Point Method (SCAIPM). iteratively linearizes objective function constraints, incorporates a barrier stability, uses Newton's method updates. efficiently handles nonconvex optimization problems improves quality dynamic IRSbased systems. simulation results show that delivers higher data rate signaltonoise ratio (SNR), low system complexity.

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Millimeter wave non-orthogonal multiple access beam management for multi-drone networks. The method involves optimizing beamforming for a master drone and multiple slave drones using channel information. It groups the slaves based on angle and solves analog and digital beamforming vectors to align beams. This enables accurate and quick beam management in high-dynamic multi-drone systems.

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Enhancing wireless communication for unmanned aerial vehicles (UAVs) using directional antennas and flight path information. The directional antennas mitigate interference by redirecting the main beam towards base stations while minimizing interference from other sources. Flight path information is used to optimize handover and interference mitigation for UAVs by leveraging the predictable aerial channel environment. This allows tailoring network parameters like handover triggers and reporting sets for different flight regions.

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Beamforming technique to improve wireless communication links between airspace network base stations and aerial vehicles like urban air mobility (UAM) aircraft. The base stations select optimal beam directions based on the known flight paths of UAM vehicles to focus the signal towards them. This mitigates interference effects specific to the airspace network environment and improves link performance compared to omnidirectional transmission.

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IRS-assisted high-speed multi-UAV communication system beam tracking to enable reliable and effective communication between ground base stations and multiple high-speed moving UAVs. The method involves using intelligent reflecting surfaces (IRS) to help align beams between the base station and UAVs. It involves predicting the UAV spatial angles, optimizing base station and IRS beamforming matrices to maximize edge UAV SNR, and aligning dual beams using the predicted angles. This improves UAV performance by leveraging IRS to compensate for mobility and external factors.

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Relay forwarding method and system for unmanned aerial vehicles (UAVs) with integrated sensing capabilities to improve millimeter wave (mmWave) relay performance. The method involves using the UAV's sensing data to accurately form mmWave beams at the user position. This mitigates errors from integrated sensing. First, the user broadcasts a centimeter wave signal, the base station feeds back confirmation, and the user selects the strongest one. Then, the UAV flies to a position with line-of-sight to both. The UAV adjusts its mmWave reflector angles based on sensed user location to form a beam. By combining centimeter feedback and sensing, the UAV finds the angles with max mmWave power at the user.

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Adaptive beam tracking method for unmanned aerial vehicle (UAV) communication that improves efficiency and performance by dynamically adjusting training frequency based on UAV motion state and optimizing beam width using a layered codebook. The steps are: 1) Estimate UAV motion state, 2) Adjust training frequency based on motion state (higher for fast motion), 3) Optimize beam width using a layered codebook, 4) Select optimal beam width based on motion state, 5) Update codebook and weights with feedback. This adapts to UAV motion and terrain for better tracking and reduces training vs fixed methods. However, it requires motion estimation and energy for adaptation.

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Sparse array of unmanned aerial vehicles (UAVs) for beamforming in three-dimensional space. The array has sparsely distributed UAVs with arbitrary spacing between them. Each UAV has an antenna. The UAVs communicate wirelessly. This allows flexible, adaptive beamforming by controlling the UAV positions and antenna phases. It enables efficient, cooperative beamforming in complex 3D environments with discontinuous spaces due to obstructions.

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Beamforming method for unmanned aerial vehicle (UAV) communications that allows rapid and accurate beam alignment between a command UAV and a mission UAV. The method uses geographic information system (GIS) data from the mission UAV to enable the command UAV to generate narrow beams pointing directly at the mission UAV. This improves tracking accuracy, UAV endurance, and data rate compared to existing beamforming techniques. The mission UAV periodically sends its GIS location to the command UAV, which uses that data to steer beams precisely at the mission UAV.

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Efficient beamforming technique for radar-communication combined systems in drones. The technique allows drones with radar and communication capabilities to operate effectively in close proximity. It involves optimizing the radar and communication beam patterns using a common design based on signal-to-noise ratio (SNR) and transmit power. This enables simultaneous radar and communication using the same beams from the drone's beamforming device.

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Multi-front switching beamforming method for active antenna arrays covering the entire airspace. It compensates for phase differences between antenna arrays when switching between fronts to maintain phase consistency for beamforming. This avoids phase jitter issues during multi-front array switching that can lead to phase inconsistency. The phase compensation algorithm is applied to the steering vectors of each front to adjust them based on the relative phase differences between the antenna arrays.

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Unmanned aerial vehicle (UAV) measurement and control method using intelligent antennas to improve UAV communication quality, range, and reliability. The method involves using an intelligent antenna array on the UAV that can adaptively steer beams in real-time based on signal analysis. This allows the UAV to dynamically align the antenna beams with ground stations and base stations to improve link quality, reduce interference, and mitigate multipath issues. The method aims to provide stable, high-quality UAV communication links using intelligent antennas.

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Beamforming method for decoupling logic beams and physical antennas in unmanned combat scenarios that allows stable communication links between drones. The method involves using a barrel-shaped array antenna that can steer beams by selecting specific antennas facing a target direction. This allows creating equal-gain seamless coverage in any horizontal plane without needing to rotate the entire array or splicing multiple arrays. This prevents issues like communication interruptions due to beam misalignment from drone movement or wind.

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Method for establishing direct communication using an unmanned aerial vehicle (UAV) with a reconfiguration intelligent surface (RIS) to provide reliable connectivity in emergency scenarios where UAVs may be deployed to areas with limited infrastructure. The method involves configuring RIS parameters based on compensating for UAV position and orientation oscillations to steer signal reflections to target areas. This mitigates loss due to uncertainty in UAV location. The RIS parameters are optimized using algorithms that consider second-order statistics of UAV vibrations.

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Applying millimeter wave (mmWave) wireless networking technology to unmanned aerial vehicles (UAVs) to enable high-speed, high-capacity UAV communications using mmWave beams. The method involves having UAVs generate beam tables based on received mmWave beams, monitor conditions for switching beams, determine target positions, move between beams, and update beam tables. The base stations transmit beams and adaptively adjust beam shapes. This allows UAVs to efficiently traverse mmWave networks with beam switching and handover.

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Adaptive beam tracking method for unmanned aerial vehicle (UAV) communications in high-speed aerial scenarios like UAV combat. The method involves generating tracking beams using channel state information (CSI) from the UAVs, but then correcting the beam directions using known flight paths of the UAVs. This improves accuracy compared to just using CSI alone. The flight path information allows adjusting the beam angles in real-time to compensate for UAV motion. It's particularly useful in dynamic aerial combat scenarios where the UAVs are moving quickly and unpredictably.

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Efficient mmWave 5G communications for unmanned aerial vehicles (UAVs) that can provide high data rate uplinks to the base station while avoiding interference to satellite receivers. The method involves determining optimal uplink beams between UAV antennas and base station receivers, since mmWave base stations with upward-facing antennas can provide higher gain to serve UAVs above horizon. The UAV provides spatial and antenna info to the base station, which configures a beam sweep of candidate pairs. The UAV then performs the sweep to find the best pair for uplink. This allows UAVs to connect to base stations with upward-facing receivers for high gain uplinks, without causing interference to satellite receivers above horizon.

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Method for enhancing communication range and quality of UAVs by using an azimuth tracking device and array antenna. The UAV initializes the azimuth of the tracking device and beam direction of the array antenna. It then uses the UAV's position to control the tracking device to compensate for horizontal angle offsets. This compensates for signal attenuation due to propagation distance by keeping the UAV's azimuth aligned with the receiver's location.

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Robust millimeter wave beamforming for unmanned aerial vehicles (UAVs) that can provide reliable and stable communication links despite UAV jitter. The method involves designing hybrid analog-digital beamforming networks for UAV base stations that can adapt to UAV motion. It models UAV jitter to predict how the UAV's motion affects the angle of signal emission. A wide beam is designed to cover the entire range of possible emission angles due to jitter. Digital beamforming is then optimized using techniques like channel estimation and power injection to balance beam width and gain. This ensures fairness and accessibility for users at all distances.

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Multi-beamforming system for tracking drone positions using fewer serial links compared to conventional systems. The system consists of a chain of beam steering blocks that receive RF signals from the drone. Each block computes partial sum beams from 1 to M indices. The blocks combine the partial sums from the previous block with their own to update the accumulated beams. The final block outputs the accumulated beams for drone location tracking. This allows tracking with fewer serial links compared to parallel transmission from all blocks.

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A method to create a mobile phased array antenna using drones that can form a directional radiation beam without the need for complex circuitry and devices compared to conventional phased array antennas. The method involves placing identical transmitting modules with antennas on drones in a line to generate a traveling wave mode. The drones fly in sequence to create the phased array. This allows directional radiation without the need for built-in shapers, circulators, phase shifters, or local oscillators. The drones can be hovering or synchronized flying.

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Method for generating a beam pattern for maintaining communication links between nodes in a moving unmanned aerial vehicle (UAV) network. The method involves estimating the UAV's spatial angle for each time frame, predicting the angle for the next frame, calculating beam boundaries based on both estimates, and generating precoding vectors to create a flat beam pattern encompassing those boundaries. This allows consistent channel gains as the UAV moves through space during a frame.

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Improving data transmission for aerial platforms like drones and high-altitude platforms by using inter-antenna beamforming between the aerial and ground antennas. The aerial antennas have variable positions and orientations. By calculating beamforming instructions based on aerial antenna positions and sending them to the ground, the ground antennas form beams that coordinate with the aerial beams. This provides high resolution and capacity between aerial and ground devices. The system leverages the flexibility of aerial antenna positions to synthesize larger beams using ground antennas.

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Method for training millimeter wave beams of unmanned aerial vehicles (UAVs) using conformal antennas to enable reliable high-speed millimeter wave communication. The method involves determining a tapered conformal antenna for the UAV, designing a layered codebook based on the antenna parameters, and performing beam training using the codebook to find optimal beams between UAVs. This allows beam alignment using the conformal antenna's wide coverage. The layered codebook structure enables fast, efficient beam training.

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Method for tracking millimeter wave communication beams between unmanned aerial vehicles (UAVs) that enables efficient beam tracking at high speeds and with posture changes. The method involves using a specific time slot structure with an exchange slot followed by tracking slots. In the exchange slot, the UAVs exchange position and attitude info via low-frequency signals. Then, in the tracking slots, the UAVs predict future positions/attitudes using machine learning and calculate predicted beam angles/vectors based on that. This allows tracking millimeter wave beams between moving UAVs that change orientation.

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Wireless communication between unmanned aerial vehicles (UAVs) and their ground stations using dynamic beamforming that adapts in real-time to the rapidly changing positions and orientations of the UAVs. Instead of relying on channel characterization and feedback, the method uses the UAV's global positioning system (GPS) and rotation sensor to directly compute the optimal beamforming direction. This eliminates the need for frequent channel training and feedback, reducing overhead and complexity. The beamformer on the UAV forms beams in the computed direction to transmit data to the ground station.

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Enhancing communication between drones and cellular networks to address the issues arising from drones operating at elevated altitudes. Solutions involve techniques like beamforming, synchronization signal design, and channel estimation optimization to mitigate coverage holes, mobility failures, and latency for drones. Beamforming helps overcome signal attenuation at high altitudes. Improved synchronization signals for 5G NR and sparse channel estimation reduce outage probability and latency. This enables reliable drone communication in 3GPP cellular networks at elevated altitudes.

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Beam tracking for millimeter wave communication between unmanned aerial vehicles (UAVs) using cylindrical conformal antennas. The method involves selecting codewords from a specialized codebook based on UAV motion to determine antenna subarrays and beamforming vectors. This allows efficient tracking of fast-moving UAVs without excessive beam switching. The codebook has layers corresponding to subarray sizes and codewords representing beam angles. By choosing the right codeword from the layer matching the UAV's motion, it selects the appropriate subarray and beamforming vector.

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Hybrid beam forming and non-orthogonal multiple access transmission method for air-to-air communication that improves spectrum efficiency and access capacity for multiple unmanned aerial vehicles (UAVs) in a system using analog beamforming and non-orthogonal multiple access. The method involves grouping UAVs into classes, optimizing beamforming for each class, and allocating power within each class using a specific algorithm. This allows maximizing capacity by leveraging hybrid beamforming and non-orthogonal multiple access techniques in air-space communication.

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Assisting autonomous flight of unmanned aerial vehicles (UAVs) using a low-cost, low-power radio beacon system that allows precise and versatile delimitation of flight zones around the beacon. The system uses adaptive beamforming to increase resolution as the UAV distance changes. It optimizes beamforming weights based on signal measurements to improve identification of delimited zones like volumes, surfaces, lines, or points. This enables accurate definition of no-fly areas and flight paths. The technique involves recursively optimizing weights using difference measurements between antenna arrays over time to compensate for UAV route variations.

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Cooperative inter-aerial antenna beamforming for communication between moving platforms like drones and user devices on the ground. The technique involves forming very narrow beams using multiple moving aerial antennas to target specific user devices. The beams are adjusted by phasing and weighting the signals from each antenna. This allows higher data rates to lower altitude user equipment compared to traditional aerial antennas. The beams are formed by determining the relative positions of the moving antennas using techniques like differential GPS. The narrow beams can be steered and focused using power measurements from the user devices.

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Beamforming technique for wireless communication in unmanned aerial vehicles (UAVs) that improves transmission performance without needing channel feedback or training signals. The technique determines the beamforming direction based on the UAV's geolocation, the remote control station's geolocation, and the UAV's rotational position. This allows dynamic beamforming without channel characterization, as the rapidly changing channel is compensated by using the UAV's movement information. The UAV's beamformer uses this direction to focus the transmission instead of relying on obsolete channel feedback.

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