3D Beamforming Research Articles

Three-dimensional grid-free sound source localization method based on deep learning

Sound source localization (SSL) technology is a popular method for identifying the locations of noise sources, which serves as a prerequisite for noise control. Deep learning, as a data-driven tool, shows broad perspectives in the field of SSL with its powerful nonlinear fitting ability. The existing deep learning-based SSL methods only provide a two-dimensional (2D) representation of the sound source location and cannot obtain the specific coordinates of the sound source in three-dimensional (3D) space. Although traditional beamforming methods can be directly generalized to 3D scenes in principle, they suffer from the limitations of insufficient vertical resolution and high computational cost. Therefore, a 3D grid-free SSL method (3DGF) informed by deep learning is suggested in this study to enhance the accuracy and computational efficiency of 3D localization. First, the number of data channels is compressed to respect limited memory resources during the training process. Subsequently, a dense convolutional neural network (DenseNet) model is utilized to obtain the 3D spatial coordinates of the sound source using the processed 3D beamforming map as input. Since the coordinates are continuous and are not constrained by the grid of the beamforming map, the grid-free strategy presents more accurate localization results. Then, the effects of the volume of training data and the compression ratio are analyzed, respectively, in simulation, and the localization performance with different signal-to-noise ratios (SNRs) is also tested. Finally, by comparing 3DGF with DAMAS, both simulation and experimental results demonstrate that 3DGF improves the accuracy and efficacy of 3D localization. Meanwhile, its satisfactory generalization ability and robustness against noise highlight its potential for practical applications.

High-Capacity Multiple-Input Multiple-Output Communication for Internet-of-Things Applications Using 3D Steering Nolen Beamforming Array

In this paper, a novel 2D Nolen beamforming phased array with 3D scanning capability to achieve high channel capacity is presented for multiple-input multiple-output (MIMO) Internet-of-Things (IoT) applications. The proposed 2D beamforming phased array is designed by stacking a fundamental building block consisting of a 3 × 3 tunable Nolen matrix, which applies a small number of phase shifters with a small tunning range and reduces the complexity of the beam-steering control mechanism. Each 3 × 3 tunable Nolen matrix can achieve a full 360° range of progressive phase delay by exciting all three input ports, and nine individual radiation beams can be generated and continuously steered on azimuth and elevation planes by stacking up three tunable Nolen matrix in horizontal and three in vertical to maximize signal-to-noise ratio (SNR) in the corresponding spatial directions. To validate the proposed design, the simulations have been conducted on the circuit network and assessed in a fading channel environment. The simulation results agree well with the theoretical analysis, which demonstrates the capability of the proposed 2D Nolen beamforming phased array to realize high channel capacity in MIMO-enabled IoT communications.

Coverage and network spectral efficiency analysis for UAV swarm under 3D beamforming in isolated regions

Coverage and network spectral efficiency analysis for UAV swarm under 3D beamforming in isolated regions

Coverage Analysis of RIS-Assisted mmWave Cellular Networks With 3D Beamforming

Coverage Analysis of RIS-Assisted mmWave Cellular Networks With 3D Beamforming

Joint 3D Deployment and Beamforming for RSMA-Enabled UAV Base Station With Geographic Information

Joint 3D Deployment and Beamforming for RSMA-Enabled UAV Base Station With Geographic Information

Volumetric beamforming in real-time using commodity hardware

Ultrasound imaging is widely used in medicine for its safety and affordability. However, it demands large transducer arrays because the image resolution is proportional to the number of elements, N, typically around 128 for 2D imaging. Three-dimensional imaging requires N2 audio channels (≈350 GB/s of data) if the equivalent 2D matrix array is used, which is practically impossible to process. To solve this issue, row-column arrays (RCAs) aggregate rows and columns of elements, reducing data rate and processing demands by a factor of N. A novel dual-stage beamforming algorithm further lowers the beamforming operations by N/2, with negligible impact on the image quality. For N = 128, the processing is 8192 times faster than with a matrix array, and it is hypothesized the 3D RCA beamforming can be done in real-time using a commodity graphics card. The beamforming rate of an NVIDIA RTX 4090 GPU was measured for in-vivo data from a rat kidney, achieving 1394 full volumes per second, which is over 150 times faster than previous implementations. Combining RCAs with the new beamforming algorithm and GPU processing thus enables volumetric beamforming to be done affordably at the bedside in real-time using a standard scanner and PC.

Design and validation of scalable reconfigurable intelligent surfaces

In this paper, we share our experience in designing, prototyping, and empirically characterizing RF Switch-based Reconfigurable Intelligent Surfaces (RIS). Our RIS design consists of arrays of patch antennas, delay lines, and programmable radio-frequency (RF) switches, enabling 3D beamforming passively, without active RF components. Our design introduces two key innovations: (i) a modular structure that provides scalability for sustainable deployments, and (ii) the support for 3-bit phase shifters, enabling high-spatial resolution codebooks. We realized this design through PCB technology and affordable electronic components, then rigorously validated our prototype in a controlled setting. With this paper, we make a comprehensive characterization of our RIS publicly available via a large dataset, to promote further empirical-driven research on this topic. Finally, we present a cost analysis of our design, which underscores the importance of sustainable practices in shaping the future of wireless technologies.

Performance Improvement Using ICIC for UAV-Assisted Public Safety Networks with Clustered Users during Emergency

The application of drones, also known as unmanned aerial vehicles deployed as unmanned aerial base stations (UABSs), has received extensive interest for public safety communications (PSC) to fill the coverage gaps and establish ubiquitous connectivity. In this article, we design a PSC LTE-Advanced air–ground-based HetNet (AG-HetNet) that is a scenario representation of a geographical area during and after a disaster. As part of the AG-HetNet infrastructure, we have UABSs and ground user equipment (GUE) flocking together in clusters at safe places or evacuation shelters. AG-HetNet uses cell range expansion (CRE), intercell interference coordination (ICIC), and 3D beamforming techniques to ensure ubiquitous connectivity. Through system-level simulations and using a brute-force technique, we evaluate the performance of the AG-HetNet in terms of fifth-percentile spectral efficiency (5pSE) and coverage probability. We compare system-wide 5pSE and coverage probability when UABSs are deployed on a hexagonal grid and for different clustering distributions of GUEs. The results show that reduced power subframes (FeICIC) defined in 3GPP Release-11 can provide practical gains in 5pSE and coverage probability than the 3GPP Release-10 with almost blank subframes (eICIC).

Low-Complexity Pareto-Optimal 3D Beamforming for the Full-Dimensional Multi-User Massive MIMO Downlink

Full-dimensional (FD) multi-user massive multiple-input multiple output (m-MIMO) systems employ large two-dimensional (2D) rectangular antenna arrays to control both the azimuth and elevation angles of signal transmission. We introduce the sum of two outer products of the azimuth and elevation beamforming vectors having moderate dimensions as a new class of FD beamforming. We show that this low-complexity class is capable of outperforming 2D beamforming relying on the single outer product of the azimuth and elevation beamforming vectors. It is also capable of performing close to its FD counterpart of massive dimensions in terms of either the users' minimum rate or their geometric mean rate (GM-rate), or sum rate (SR). Furthermore, we also show that even FD beamforming may be outperformed by our outer product-based improper Gaussian signaling solution. Explicitly, our design is based on low-complexity algorithms relying on convex problems of moderate dimensions for max-min rate optimization or on closed-form expressions for GM-rate and SR maximization.

Robust 3D Beamforming for Secure UAV Communications by DAE

Robust 3D Beamforming for Secure UAV Communications by DAE

Specific order and bisection search aided joint 3D beamforming and RIS reflecting optimization

In this paper, a three-node transmission model is conceived, where the base station (BS) node leverages 3D beamforming, the reconfigurable intelligent surface (RIS) node can constructively reconfigure the wireless channel, the user node only has a single antenna due to a limited price. Maximization of its downlink spectral efficiency is a joint optimization problem of three variables, namely phase-shift matrix Φ of RIS, tilt angle θ and beamforming vector w used in BS 3D beamforming. We solve this problem by employing the alternating optimization (AO) algorithm. But, in each iteration, a specific optimization order of firstly Φ, secondly θ and finally w is proposed, which facilitates the search of optimal θ in the way of narrowing its trust region and enabling unimodal property over the narrowed trust region. It finally results in a better combination of {Φ, θ, w}.

Resource Management for Collaborative 5G-NR-V2X RSUs to Enhance V2I/N Link Reliability.

In the development of autonomous driving technology, 5G-NR vehicle-to-everything (V2X) technology is a key technology that enhances safety and enables effective management of traffic information. Road-side units (RSUs) in 5G-NR V2X provide nearby vehicles with information and exchange traffic, and safety information with future autonomous vehicles, enhancing traffic safety and efficiency. This paper proposes a communication system for vehicle networks based on a 5G cellular network with RSUs consisting of the base station (BS) and user equipment (UE), and validates the system performance when providing services from different RSUs. The proposed approach maximizes the utilization of the entire network and ensures the reliability of V2I/V2N links between vehicles and each RSU. It also minimizes the shadowing area in the 5G-NR V2X environment, and maximizes the average throughput of vehicles through collaborative access between BS- and UE-type RSUs. The paper applies various resource management techniques, such as dynamic inter-cell interference coordination (ICIC), coordinated scheduling coordinated multi-point (CS-CoMP), cell range extension (CRE), and 3D beamforming, to achieve high reliability requirements. Simulation results demonstrate improved performance in outage probability, reduced shadowing area, and increased reliability through decreased interference and increased average throughput when collaborating with BS- and UE-type RSUs simultaneously.

3-D Hybrid Beamforming for Terahertz Broadband Communication System With Beam Squint

In this paper, the three-dimensioned (3D) hybrid beamforming is designed for the terahertz (THz) based broadband broadcasting communication system with beam squint. Specifically, the full-dimensional THz massive multiple input multiple output (M-MIMO) channel model and the array gain of the uniform planar array (UPA) are first analyzed in the context of the beam squint effect. Then, a 3D hybrid beamforming architecture is proposed by leveraging two-tier true time delay (TTD), which is able to combat the beam squint effect from the horizontal and vertical directions. To further reduce hardware cost and power consumption, a low-cost 3D hybrid beamforming architecture with a two-tier TTD and phase shifter combination (TPC) is designed. Simulation results are shown that the performance of the proposed 3D hybrid beamforming architectures is capable of approaching that of the full-digital beamforming counterpart in the face of beam squint, despite relying on reduced implementation cost.

Antenna Array Diversity Evaluation Under Multipath Environments With Digital Beamforming

This work proposes a methodology for evaluating the antenna array diversity and resultant radiation pattern from digitally-processed-based beamforming systems. Our approach enables to interpret the advanced antenna systems (AAS) coverage and massive multiple-input multiple output (mMIMO) spatial resolution, by the inspection of the array resultant multiple beams. Particularly, the impact on the mMIMO spatial resolution is conducted as a function of the channel correlation, by means of an exclusively radiofrequency (RF) approach, with the advantage of not considering the system-level features, and using a new figure of merit (factor). The new figure of merit enables to evaluate the antenna array diversity from two-and three-dimensional (2D and 3D) beamforming, by computing the number of lobes with gain higher than a unique element. In the 3D case, the figure of merit is based on a differential calculation, which enables performing an infinitesimal counting of lobes per antenna element beamwidth. Such parameter is initially applied to a theoretical dipole-based array, with the purpose of quantifying the created multiple beams by the overlapped radiation patterns from mMIMO systems. Furthermore, the factor is exploited for analyzing the performance of a 64-element and dual-polarized SICL-based slot antenna array and a 64-element dipole-based antenna prototypes, both previously developed by our research group. Finally, it is demonstrated that the factor increases as diversity increases and dipole-based antenna array could be used as an upper limit, attaining 11.46 lobes/rad.

Optimized auto-focusing method for 3D ultrasound imaging in NDT

In this work, we propose an optimized auto-focusing algorithm to be used with ultrasound matrix arrays for three-dimensional imaging in the presence of interfaces. Its main application is for non-destructive-testing (NDT), where usually two mediums with different propagation velocities are present. The refraction at the interface between those mediums complicates the calculation and the application of the focusing delays, which requires iterative processes that are usually the main bottleneck for high-speed inspections.We tackle this problem by generalizing the virtual array concept previously proposed for linear arrays and plane images to the case of matrix-arrays and three-dimensional (3D) beamforming. Furthermore, we propose a two-dimensional iterative algorithm for exact time-of-flight calculation to the two foci per scan line required by the virtual array. The mathematical formulation for the 3D case is obtained and the time-delay errors are analyzed by simulation. Finally, image quality with the proposed method is compared with that obtained with conventional Total Focusing Method (TFM) and exact delay calculation. The principal conclusion is that the virtual array approach generates images with equivalent quality to those obtained by exact calculation, while it reduces more than two orders of magnitude the computation load.

3D beamforming in Intelligent Reflecting Surface (IRS)-assisted multi-user cognitive radio networks

In this paper, we consider a multi-user cognitive radio network (CRN) equipped with an intelligent reflecting surface (IRS). We examine the network performance by evaluating the fairness of the secondary system, which is satisfying the minimum required signal to interference and noise ratio (SINR) for each secondary user (SU). The minimum SINR of the SUs is maximized by joint optimization of the beamforming vector and three-dimensional beamforming (3DBF) angles at the secondary base station (SBS) and also the phase shifts of the IRS elements. This optimization problem is highly non-convex. To solve this problem, we utilize Dinkelbach’s algorithm along with an alternating optimization (AO) approach to achieve some sub-problems. Accordingly, by further applying a semi-definite relaxation method, we convert these sub-problems to equivalent convex forms and find a solution. Furthermore, analytically we propose an algorithm for optimizing 3DBF angles at the SBS. Through numerical results, the improvement of the sum SINR of the secondary system using the proposed method is illustrated. Moreover, it is shown that as the number of reflecting elements of IRS increases, the sum SINR significantly augments while satisfying fairness. Also, the convergence of the proposed algorithm is verified utilizing numerical results.

A Dual Polarization 3-D Beamforming AiP

This paper describes the implementation of an antenna-in-package (AiP) with a dual polarization function, supporting a three-dimensional (3D) beamforming operation. In order to implement 3D beamforming, a Yagi-type end-fire antenna supporting each of the x and y directions and a patch-type broadsided antenna supporting the z-direction were implemented. The broadside antennas have dual polarization functions so that they can be received in any direction. Each antenna was implemented in four array structures to support beamforming operations. The broadside antenna was designed in a 2 × 2 array structure, with a patch-type antenna and two linear dual polarization functions. The single antenna operated with a gain of 6 dBi, an E-plane beam width of ±45 degrees, and an H-plane beam width of ±50 degrees and had an antenna gain of 9~11 dBi as well as a vertical/horizontal forming operation with a radiation angle of ±22 degrees The end-fire antenna unit was designed in a 1 × 4 array structure with a Yagi-type antenna. The single antenna had a gain of 4 dBi, with an antenna gain of 8 dBi in the array structure, and it was improved to 11 dBi by adding a parasitic array director. The final end-fire antenna unit had a radiation angle of ±11 degrees and a beamforming coverage of ±45 degrees The vertical and horizontal design results were secured for reception in any direction, and all the array antennas had a return loss of 10 dB or less in the entire frequency band, from 57 to 66 GHz.

Achieving high-resolution 3D acoustic imaging in a large-aspect-ratio cabin by the non-synchronous measurements

The resolution of conventional acoustic imaging methods in a large-aspect-ratio cabin is reduced seriously by array parameters limitation and reverberation. The non-synchronous measurements technique breaks through the limitation of array shape and the number of microphones. This method can approximate the result of synthetic large-aperture array acoustic imaging. The increase in the number of microphones and low-rank constraint assumption in non-synchronous measurements suppress the reverberation interference. The low-rank constraint filters out the eigenvalues of the reverberation sound other than the main noise sources, which is acted as an eigenvalue filter. It has been demonstrated that non-synchronous measurements with 3D beamforming can improve the resolution of acoustic imaging in cubic space, but the related research on the large-aspect-ratio cabin is still missing. The non-synchronous measurements method is applied to achieve high-resolution acoustic imaging in a large-aspect-ratio cabin in this paper. The array measurement scheme is investigated comprehensively, including the number of non-synchronous measurements, the array step distance and appropriate spatial basis functions. The experimental results show that the non-synchronous measurements can achieve high-resolution 3D acoustic imaging in the cabin of an urban rail vehicle.

Optimum Extrapolation Techniques for Two-Dimensional Antenna Array Tapered Beamforming

Optimizing antenna arrays is essential for achieving efficient beamforming with very low sidelobe level (SLL) where adopting tapered window functions is one of the straightforward efficient techniques for achieving this goal. Recently, two-dimensional (2D) beamforming has been extensively required for many applications; therefore, this paper proposes two extrapolation techniques applied to one-dimensional (1D) tapered functions to efficiently feed 2D antenna arrays using cross-linear and adaptive radial tapering techniques. The first proposed 2D cross-linear tapering technique determines the 2D tapering coefficients by Hadamard multiplication of two right-angled grids of repeated 1D functions, while the second proposed adaptive radial tapering technique locates the antenna element in the 2D array in terms of its radial distance with respect to the array center, then converts this distance to an element index in a virtual 1D tapering window to determine the element weighting value. The adaptive radial tapering technique is optimized for achieving the minimum SLLs. The two proposed techniques are analyzed and discussed, where it is found that the adaptive radial tapering provides deeper SLLs compared to the cross-linear tapering technique. The two extrapolation techniques are examined for four window functions including triangular (Bartlett), Hamming, cosine-square, and Blackman windows, and the simulation results show that for extrapolating the Blackman window using adaptive radial tapering, a –50 dB SLL can be achieved which is independent on the array size, while cross-linear tapering provides –35 dB and –41 dB SLLs for and antenna arrays, respectively.

Improving Quality-of-Service in Cluster-Based UAV-Assisted Edge Networks

With millions of devices connected together, the Internet of Things (IoT) has become an emerging technology for future wireless networks. The ever-increasing number of smart devices and data hungry applications demand a high Quality-of-Service (QoS) for IoT. In conventional networks, data being sent to cloud for computational purpose leads to poor QoS. In order to address QoS challenges, mobile edge networks have emerged as a promising solution. In edge networks, bringing the networks resources closer to the end devices results in improved QoS. The maneuverability and the ease of versatile deployment coupled with cost efficiency makes unmanned aerial vehicles (UAVs) a promising candidate for future edge networks. The UAVs can act as edge servers to provide computational capabilities and improved services to the edge devices. Due to the flying ability, UAVs can establish better line-of-sight link with the ground devices. In this paper, we consider that the edge devices in the area of interest have to be facilitated with a certain desired QoS, which is based on the notion of outage probability of the wireless link between the UAV and the edge devices. In this context, we first propose a novel method that computes the optimum height at which UAV should hover, resulting in maximum coverage radius with sufficiently small outage probability. Then the geographical area is divided in optimal number of clusters using a novel algorithm based on K-means clustering. The method computes the optimum number of UAVs required for covering the area of interest. Each of the UAVs utilizes 3D beamforming in order to cover its own coverage area. For this purpose, we are taking coordinate transformation of the original area and forming a wide beam to cover the desired area. The obtained results demonstrate the effectiveness of the proposed method when compared to existing methods, which validate the utilization of the proposed method over large scale network applications.