Beamforming Techniques Research Articles

Contrast-free microvessel imaging using null subtraction imaging combined with harmonic imaging

Ultrasound localization microscopy (ULM) has superior spatial resolution; however, it requires contrast agents and long data acquisition and processing time. Null subtraction imaging (NSI) is a nonlinear beamforming technique that improves the spatial resolution and reduces grating lobes with low computational cost. We combined pulse-inversion (PI) nonlinear imaging with NSI to increase resolution. Pulses with center frequency of 10.42 MHz and its inverted version were transmitted to obtain the second harmonic at 20.84 MHz (wavelength of ∼74 μm). The transducer pitch was 35% larger than the wavelength of the receive signal, which would introduce grating lobes in the field of view. A total of 1000, 9-angle (−8 to 8 degree in 2 degrees step) coherently compounded frames were acquired in 1 s. SVD filters were applied in raw RF data to filter out tissue signal. The dc offset was set to 0.1 in NSI imaging. Grating lobes, which were obvious in DAS images, were removed in the NSI images. Higher spatial resolution and contrast were observed from the NSI microvessel images. The spatial resolution of the NSI images using harmonic imaging approached one fourth of a wavelength with computation time increased by only 40% compared to DAS.

Contextual beamforming: Exploiting location and AI for enhanced wireless telecommunication performance

Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users’ location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages, and implications. Notably, we demonstrate an impressive 53% improvement in the signal-to-interference-plus-noise ratio by implementing the adaptive beamforming maximum ratio transmission (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of artificial intelligence (AI) schemes, including machine learning and deep learning, in implementing contextual beamforming techniques that leverage user location information. Based on the comprehensive review, the results suggest that the combination of MRT and zero-forcing techniques, alongside deep neural networks employing Bayesian optimization, represents the most promising approach for contextual beamforming. Furthermore, the study discusses the future potential of programmable switches, such as Tofino—an innovative switch developed by Barefoot Networks (now a part of Intel)—in enabling location-aware beamforming. This paper highlights the significance of contextual beamforming for improving wireless telecommunications performance. By capitalizing on location information and employing advanced AI techniques, the field can overcome challenges and unlock new possibilities for delivering reliable and efficient mobile networks.

Orthogonal beamforming technique for massive MIMO systems

AbstractBeamforming represents a pivotal technology in massive multiple-input multiple-output (MIMO) systems, as it facilitates the regulation of transmission and reception operations. Beamforming techniques’ categorization is based either on their hardware architecture or implementation strategy. This paper proposes an orthogonal beamforming technology founded on a specific implementation method that utilizes predetermined orthogonal beams to serve users. The suggested approach incorporates numerous orthogonal beams relying on a substantial number of antennas at the base station. The primary objective of this approach is to enhance the performance of massive MIMO systems by augmenting spectral efficiency and accommodating more users. The proposed beamforming approach is well suited for millimeter frequency bands. The purpose of this paper is to explore the suggested orthogonal beamforming technology. The concept of this approach is described at first and then followed by an evaluation of its efficacy for a single user through the allocation of orthogonal beams. The suggested approach is also examined in the context of multiuser systems, and the results are compared with the adaptive ZF beamforming technique. Furthermore, the paper presents solutions to the issues that may arise in multiuser systems, for example, ensuring that each orthogonal beam is assigned to only one user. The simulations conducted in this study demonstrate that the suggested approach outperforms the ZF technique in terms of both the spectral efficiency and the number of serviced users. Specifically, the suggested approach can enhance SE by approximately 40.6% over the ZF technique, and it can support up to double the number of users when compared to the ZF approach.

A review of beamforming microstrip patch antenna array for future 5G/6G networks

With the increase in demand for high data rates and high bandwidth because of multiple users all over the globe, the technology has moved toward the next-generation of wireless communication. This rapid advancement of wireless communication technologies has led to the emergence of 5G networks, which promise significantly higher data rates, lower latency, and enhanced connectivity. Researchers believe that five essential techniques can enable 5G. Beamforming is one of those essentials, as it plays a vital role in achieving reliable and high-capacity communication. This review article portrays a comprehensive analysis of the 5G beamformer Microstrip Patch Antenna array techniques for communication systems. The paper comprises of a deep overview of the fundamental concepts and principles of beamforming, including analog, hybrid, and digital beamforming techniques. It explores the advantages and disadvantages of each approach and discusses their suitability for 5G applications. An in-depth examination of various beamforming techniques employed in 5G, encompassing traditional beamforming, massive Multiple-Input-Multiple-Output beamforming, hybrid beamforming, and adaptive beamforming. The discussion encompasses the strengths, weaknesses, and performance trade-offs of each technique, along with their applicability in diverse deployment scenarios and applications. The review of multiple couplers that are used for the feeding of the antenna is discussed with included hybrid coupler, Wilkinson power divider, branch line coupler, and butler matrix in beamformer smart antenna for 5G/6G communications. Numerous beamforming techniques are compared based on their merits, demerits, and applications. Moreover, the dielectric substrate utilized to design the beamformer was also reviewed. The findings presented in this paper serve as a valuable resource for the researcher, scholars, and engineers working in the field of 5G wireless communications and antenna designing, facilitating the development and deployment of efficient and robust beamforming solutions for future 5G networks.

Mainlobe deceptive jammer suppression with DEPC-MIMO radar with joint transmit–receive design

This paper investigates the problem of mainlobe deceptive jammer suppression via joint transmit–receive design in a multiple-input multiple-output (MIMO) radar. At the design stage, a discrete element-pulse coding (DEPC) phase is implemented in both the slow-time pulses and transmit array antennas. After decoding and compensation of the delayed pulses, the true and false targets can be identified in the joint transmit–receive (JTR) spatial frequency domain. Furthermore, to eliminate the false targets, a data-dependent beamforming technique is adopted, where an optimization problem is constructed to maximize the output signal-to-interference-plus-noise ratio (SINR) by optimizing the DEPC coefficients and the weight vector of the receive filter in an alternating way. Specifically, two methods, including the Single Jammer Suppression (SJS)-Alternating Direction Method of Multipliers (ADMM) and Multiple Jammers Suppression (MJS)-Gradient Descent (GD) methods are developed for the cases of a single jammer and multiple jammers, respectively. A series of numerical results are utilized to verify the effectiveness of the proposed methods for mainlobe deceptive jammer suppression.

Novel techniques for in situ estimation of shear-wave velocity and damping ratio through MASW testing – I: a beamforming procedure for extracting Rayleigh-wave phase velocity and phase attenuation

SUMMARY A robust, in situ estimate of shear-wave velocity VS and the small-strain damping ratio DS (or equivalently, the quality factor QS) is crucial for the design of buildings and geotechnical systems subjected to vibrations or earthquake ground shaking. A promising technique for simultaneously obtaining both VS and DS relies on the Multichannel Analysis of Surface Waves (MASW) method. MASW can be used to extract the Rayleigh wave phase velocity and phase attenuation data from active-source seismic traces recorded along linear arrays. Then, these data can be inverted to obtain VS and DS profiles. This paper introduces two novel methodologies for extracting the phase velocity and attenuation data. These new approaches are based on an extension of the beamforming technique which can be combined with a modal filter to isolate different Rayleigh propagation modes. Thus, the techniques return reliable phase velocity and attenuation estimates even in the presence of a multimode wavefield, which is typical of complex stratigraphic conditions. The reliability and effectiveness of the proposed approaches are assessed on a suite of synthetic wavefields and on experimental data collected at the Garner Valley Downhole Array and Mirandola sites. The results reveal that, under proper modelling of wavefield conditions, accurate estimates of Rayleigh wave phase velocity and attenuation can be extracted from active-source MASW wavefields over a broad frequency range. Eventually, the estimation of soil mechanical parameters also requires a robust inversion procedure to map the experimental Rayleigh wave parameters into soil models describing VS and DS with depth. The simultaneous inversion of phase velocity and attenuation data is discussed in detail in the companion paper.

Robust Beamforming Design for an IRS-Aided NOMA Communication System With CSI Uncertainty

Intelligent reflecting surface (IRS) is a promising technology that provides high throughput in future communication systems and is compatible with various communication techniques, such as non-orthogonal multiple-access (NOMA). This paper studies the downlink transmission of IRS-assisted NOMA communication, considering the practical case of imperfect channel state information (CSI). Aiming to maximize the system sum rate, a robust IRS-aided NOMA design is proposed to jointly find the optimal beamforming vector for the access point and the passive reflection matrix for the IRS. This robust design is realised using the penalty dual decomposition (PDD) scheme, and it is shown that the results have a close performance to their upper bound obtained from the corresponding perfect CSI scenario. The presented method is compatible with both continuous and discrete phase shift elements of the IRS. Our findings show that the proposed algorithms, for both continuous and discrete IRS, have low computational complexity compared to other schemes in the literature. Furthermore, we conduct a performance comparison between the IRS-aided NOMA and the IRS-aided orthogonal multiple access (OMA). This comparison shows that robust beamforming techniques are crucial for the system to reap the advantages of IRS-aided NOMA communication in the presence of CSI uncertainty.

Further Development of Rotating Beamforming Techniques Using Asynchronous Measurements

When rotating noise sources, such as turbomachinery, are investigated using phased microphone array measurements and beamforming, sidelobes appear on the resulting beamforming maps. Sidelobes can be decreased by increasing the number of microphones. However, if the investigated phenomenon is steady, then there is a cost-effective alternative: performing asynchronous measurements using phased arrays having a limited number of microphones. The single beamforming maps can be combined in order to arrive at results that are superior in resolution and sidelobe levels. This technique has been investigated in the literature, but according to the authors’ best knowledge, has not yet been applied to turbomachinery. This article introduces a means for applying the asynchronous measurement technique and the combination methods for rotating noise sources. The combination methods are demonstrated on two rotating point sources (both in simulations and measurements), and then on an axial flow fan test case. In the case of the two rotating point sources, the achievable improvement in resolution, average-, and maximum sidelobe levels are shown as compared to the single results. In the case of the axial flow fan, it is demonstrated that the combination methods provide more reliable noise source locations and reveal further noise sources.

Outage performance and energy efficiency optimization of wireless-powered millimeter-wave sensor networks

AbstractWith the widespread use of wireless sensor networks, one of the most pressing concerns is extending the lifetime of the sensors. By deploying directional antenna arrays, millimeter wave (mmWave) is a possible candidate for wireless energy transfer (WPT). This paper investigates a beneficial combination of WPT and data transmission in a typical mmWave sensor network with Rayleigh channels, where a transmission interval can be divided into two sub-intervals. During the first sub-interval, one hybrid access point (HAP) employs beamforming techniques to transfer energy for serving multiple sensors within the service sector. The sensors then transmit their individual signal in turn to the HAP based on time division multiple address (TDMA) strategy by using the whole harvested energy. According to stochastic geometry, the exact and approximate expressions of beam outage probability for the considered system are determined, respectively. The optimal time allocation of energy harvesting and data transmission for sensors is examined in order to maximize the energy efficiency of the system. The optimization problem can be translated into corresponding parametric form, and the resulting optimization problem can be solved using the Lagrange dual method with Karush–Kuhn–Tucker (KKT) conditions. The numerical results show the variation trend of the beam outage probability under various parameters and verify the accuracy of the theoretical analyses. Furthermore, the simulation results illustrate that the proposed optimal time allocation strategy can significantly enhance the overall energy efficiency of the system compared with a similar scheme.

Molecular Beamforming for Actuation in Molecular Communication Networks.

The actuation accuracy of sensing tasks performed by molecular communication (MC) schemes is a very important metric. Reducing the effect of sensors fallibility can be achieved by improvements and advancements in the sensor and communication networks design. Inspired by the technique of beamforming used extensively in radio frequency communication systems, a novel molecular beamforming design is proposed in this paper. This design can find application in tasks related to actuation of nano machines in MC networks. The main idea behind the proposed scheme is that the utilization of more sensing nano machines in a network can increase the overall accuracy of that network. In other words, the probability of an actuation error reduces as the number of sensors that collectively take the actuation decision increases. In order to achieve this, several design procedures are proposed. Three different scenarios for the observation of the actuation error are investigated. For each case, the analytical background is provided and compared with the results obtained by computer simulations. The improvement in the actuation accuracy by means of molecular beamforming is verified for a uniform linear array as well as for a random topology.

A Multi-Mode Superposition Technique for Circular Polarized Beamforming and Steering in Mobile Communication and Radar Systems

A Multi-Mode Superposition Technique for Circular Polarized Beamforming and Steering in Mobile Communication and Radar Systems

Low-Complexity Uncertainty-Set-Based Robust Adaptive Beamforming for Passive Sonar

Recent work has highlighted the potential benefits of exploiting ellipsoidal uncertainty-set-based robust Capon beamformer (RCB) techniques in passive sonar. Regrettably, the computational complexity required to form RCB weights is cubic in the number of adaptive degrees of freedom, which is often prohibitive in practice. For this reason, several low-complexity techniques for computing RCB weights, or equivalent worst case robust adaptive beamformer weights, have recently been developed. These techniques, whose complexities are only quadratic in the number of adaptive degrees of freedom, use gradient-based, reduced-dimension Krylov-subspace or Kalman-filtering methods. In this work, we review these techniques for passive sonar, analyzing their complexities and evaluating them initially on simulated data. The best performing methods are then evaluated on two in-water recorded passive sonar data sets. One set, containing a strong controlled acoustic source, demonstrates the ability of the algorithms to protect against signal cancellation when pointing at the source, and their ability to reject the source when pointing away from it. The other data set, recorded during a period when the boat was accelerating, demonstrates the ability of the algorithms to operate in the presence of speed-induced noises.

Power Optimization of Unmanned Aerial Vehicle-Assisted Future Wireless Communication Using Hybrid Beamforming Technique in Disaster Management

Several established procedures are required to be followed when responding to disasters. Although most of them have so far been successful, they pose their own set of difficulties. The primary factor is response time, which is crucial for disaster management. The use of unmanned aerial vehicles (UAVs) for wireless communication not only increases response time but also is energy efficient. However, UAVs have limited power capacities, which makes their use in wireless communication challenging. In wireless communication, hybrid beamforming is a technique for optimizing the battery consumption of unmanned aerial vehicles (UAVs). Massive MIMO technology facilitates hybrid beamforming by deploying antenna arrays, efficiently directing transmitted energy to intended receivers, and minimizing power waste. Beamforming relies heavily on accurate Channel State Information (CSI). Advanced channel estimation and tracking techniques optimize power allocation based on real-time channel conditions, thereby minimizing energy consumption and ensuring connection reliability. Hybrid beamforming combines the advantages of digital and analog beamforming to reduce power consumption while maintaining communication performance. This paper proposes a power optimization technique for UAV-based wireless communication using hybrid beamforming to maximize spectral efficiency and increase the battery life of UAVs.

Windowed Radon Transform and Tensor Rank-1 Decomposition for Adaptive Beamforming in Ultrafast Ultrasound.

Ultrafast ultrasound has recently emerged as an alternative to traditional focused ultrasound. By virtue of the low number of insonifications it requires, ultrafast ultrasound enables the imaging of the human body at potentially very high frame rates. However, unaccounted for speed-of-sound variations in the insonified medium often result in phase aberrations in the reconstructed images. The diagnosis capability of ultrafast ultrasound is thus ultimately impeded. Therefore, there is a strong need for adaptive beamforming methods that are resilient to speed-of-sound aberrations. Several of such techniques have been proposed recently but they often lack parallelizability or the ability to directly correct both transmit and receive phase aberrations. In this article, we introduce an adaptive beamforming method designed to address these shortcomings. To do so, we compute the windowed Radon transform of several complex radio-frequency images reconstructed using delay-and-sum. Then, we apply to the obtained local sinograms weighted tensor rank-1 decompositions and their results are eventually used to reconstruct a corrected image. We demonstrate using simulated and in-vitro data that our method is able to successfully recover aberration-free images and that it outperforms both coherent compounding and the recently introduced SVD beamformer. Finally, we validate the proposed beamforming technique on in-vivo data, resulting in a significant improvement of image quality compared to the two reference methods.

New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

Reduced-resolution beamforming: Lowering the computational cost for pulsar and technosignature surveys

Abstract In radio astronomy, the science output of a telescope is often limited by computational resources. This is especially true for transient and technosignature surveys that need to search high-resolution data across a large parameter space. The tremendous data volumes produced by modern radio array telescopes exacerbate these processing challenges. Here, we introduce a ‘reduced-resolution’ beamforming approach to alleviate downstream processing requirements. Our approach, based on post-correlation beamforming, allows sensitivity to be traded against the number of beams needed to cover a given survey area. Using the MeerKAT and Murchison Widefield Array telescopes as examples, we show that survey speed can be vastly increased, and downstream signal processing requirements vastly decreased, if a moderate sacrifice to sensitivity is allowed. We show the reduced-resolution beamforming technique is intimately related to standard techniques used in synthesis imaging. We suggest that reduced-resolution beamforming should be considered to ease data processing challenges in current and planned searches; further, reduced-resolution beamforming may provide a path to computationally expensive search strategies previously considered infeasible.

HYBRID BEAMFORMING FOR MULTIBEAM PHASED ARRAY RECEVIERS

In the search for enhanced wireless communication systems, multibeam phased array receivers have gained prominence. They promise to significantly boost data rates, reduce latency, and improve reliability. However, implementing multibeam receivers with traditional beamforming techniques can be challenging due to the high computational demands and the need for multiple radio frequency (RF) chains. Hybrid beamforming combines the advantages of digital and analog beamforming to strike a balance between performance and complexity. Our research delves into the following aspects of Hybrid beamforming for multibeam phased array receivers: Reduced Hardware Complexity: By blending digital and analog beamforming, we reduce the number of required RF chains, making multibeam receivers more cost-effective. Enhanced Beam Steering: Hybrid beamforming maintains precise control over multiple beams, ensuring efficient signal reception and transmission. Real-World Applications: We discuss practical applications in 5G and beyond, satellite communications, and radar systems. The paper delves into the fundamental concepts of analog and digital beamforming, illustrating their respective strengths and limitations. It then presents the architecture of hybrid beamforming systems, emphasizing the synergistic integration of analog and digital components. Special attention is given to the design considerations of beamforming networks, antenna arrays, and the beam steering mechanism. KEYWORDS Hybrid Beamforming , Phased Array , Multi-Beam , Analog Beamforming , Digital Beamforming , Beamforming Networks , Antenna Array , Beam Steering , Spatial Multiplexing , Precoding , Channel Estimation , Interference Mitigation , Power Consumption , Millimeter Wave (mmWave) , 5G and Beyond .

A Novel Intrapulse Beamsteering SAR Imaging Mode Based on OFDM-Chirp Signals

The multiple-input multiple-output synthetic aperture radar (MIMO SAR) system has developed rapidly since its discovery. At the same time, the low-disturbance and high-gain requirements of the MIMO system are continuing to increase. Through the application of digital beamforming (DBF) techniques, the multidimensional waveform encoding (MWE) technique can play a key role in MIMO systems, which can greatly improve the system’s performance, especially the multi-mission capability of radar. Intrapulse beamsteering in elevation is a typical form of multi-dimensional waveform encoding which can greatly improve the transmitting efficiency and multi-mission performance of radar. However, because of the high sensitivity of the DBF technique to height, there is significant deterioration in performance in the presence of terrain undulations. The OFDM (Orthogonal Frequency Division Multiplexing) technique is widely used in communication. Due to the similarity of radar and communication systems and the great waveform diversity of OFDM signals, the OFDM radar has recently begun to emerge as a new radar system, simultaneously, the orthogonality of OFDM signals is in the time and frequency domains, and is not affected by terrain undulation. So, this paper proposes a novel radar mode combining intrapulse beamsteering in elevation and OFDM-Chirp signals, that is, the combination of “beam orthogonality” and “waveform orthogonality”, which can greatly improve the performance and fault tolerance to interference signals. In this manuscript, the system working mode and signal processing flow are introduced in detail, and simulations for both point targets and distributed targets are carried out to verify the feasibility of the proposed mode. Simultaneously, a comparison experiment is carried out, which shows the high level of fault tolerance to terrain undulation and the high potential of the proposed radar mode in Earth observation.

A novel semi-blind source separation framework towards maximum signal-to-interference ratio

For the independence-based blind source separation (BSS) methods, effective modeling of the source signals is important. When applying the auxiliary function techniques, different source models normally result in different forms of the weighted covariance matrices, which in turn are used to compute the demixing filters. This paper proposes a new algorithmic framework termed minimum variance independent component analysis (MVICA), which is rigorously derived from the conventional BSS methods by determining the weighted covariance matrices with the maximum signal-to-interference ratio (SIR) criterion.The maximum-SIR weighted covariance matrix is approximately proved to be the interference covariance matrix. A deep neural network-supported implementation of the proposed MVICA algorithm is subsequently presented. Furthermore, we give a revealing insight into the relationships between MVICA and the existing speech separation approaches including conventional BSS methods and several mainstream beamforming techniques. Experimental results show the superiority of MVICA over the state-of-the-art BSS techniques and beamformers under various conditions, in terms of not only SIR but also signal-to-distortion ratio, speech intelligibility and perceptual quality and automatic speech recognition accuracy.

Performance Enhancement of VLC-NOMA Employing Beamforming Function based Vehicle-to-Multivehicle Communication System

The realm of vehicular safety applications driven by communication has surfaced as a paramount approach for elevating road safety standards. The adoption of Vehicular VLC (V-VLC) is rooted in its multifaceted advantages, making it a preferred choice for integrating both illumination and data transmission. Beyond its highly secure attributes, V-VLC boasts virtues such as demonstrating low complexity, and ensuring immunity to radio frequency (RF) interference. The core premise of this study revolves around the proposition of a novel system that synergistically integrates NOMA into V-VLC networks to amplify spectral efficiency, harnesses beamforming techniques to bolster Signal-to-Noise Ratio (SNR), and leverages Successive Interference Cancellation (SIC) to curtail interference. An exhaustive analysis of this system configuration is provided, accompanied by the derivation of a precise Signal-to-Interference-plus-Noise Ratio (SINR) expression tailored to the proposed scenario. This paper not only delves into the nuanced aspects of NOMA performance at the receiver but also delves into critical dimensions such as the influence of transmitter-receiver distance, elevation disparity between transmitter and receiver, and the impact of diverse channel conditions on received power and BER VS. Eb/No for different MIMO configurations.