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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