Journal articles: 'Passive Beamforming'

1

Gao, Jiabao, Caijun Zhong, Xiaoming Chen, Hai Lin, and Zhaoyang Zhang. "Unsupervised Learning for Passive Beamforming." IEEE Communications Letters 24, no. 5 (May 2020): 1052–56. http://dx.doi.org/10.1109/lcomm.2020.2965532.

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Di Martino, Gerardo, and Antonio Iodice. "Passive beamforming with coprime arrays." IET Radar, Sonar & Navigation 11, no. 6 (June 2017): 964–71. http://dx.doi.org/10.1049/iet-rsn.2016.0517.

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Jung, Minchae, Taehyoung Kim, and Hyukmin Son. "Performance Analysis of RIS-Assisted SatComs Based on a ZFBF and Co-Phasing Scheme." Mathematics 12, no. 8 (April 21, 2024): 1257. http://dx.doi.org/10.3390/math12081257.

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In recent high-throughput satellite communication (SatCom) systems, the use of reconfigurable intelligent surfaces (RISs) has emerged as a promising solution to improve spectral efficiency and extend coverage in areas with limited terrestrial network access. However, the RIS may amplify the inter-beam interference (IBI) caused by multibeam transmission at the satellite, and multiple RISs can also cause inter-RIS interference (IRI) to terrestrial users. In this paper, the performance of the RIS-assisted SatCom system is asymptotically analyzed for both full and partial channel state information (CSI) scenarios. In particular, zero-forcing beamforming is considered as the active beamforming for data transmission, while the co-phasing scheme is considered as the passive beamforming for RIS reflection. Based on the asymptotic analyses, deterministic active and passive beamforming techniques using partial CSI are proposed that can gradually eliminate both IBI and IRI, ultimately achieving ideal performance. Simulation results validate the accuracy of asymptotic analyses and demonstrate the superiority of deterministic active and passive beamforming techniques using partial CSI. The simulation results also confirm that the proposed beamforming can achieve approximately 92.8% of the ideal performance, even though it only requires partial CSI.

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Gao, Chuanzhe, Shidang Li, Yixuan Wu, Siyi Duan, Mingsheng Wei, and Bencheng Yu. "Power-Efficient Resource Allocation for Active STAR-RIS-Aided SWIPT Communication Systems." Future Internet 16, no. 8 (July 25, 2024): 266. http://dx.doi.org/10.3390/fi16080266.

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Simultaneous wireless information and power transfer (SWIPT) has emerged as a pivotal technology in 6G, offering an efficient means of delivering energy to a large quantity of low-power devices while transmitting data concurrently. To address the challenges of obstructions, high path loss, and significant energy consumption associated with long-distance communication, this work introduces a novel alternating iterative optimization strategy. The proposed approach combines active simultaneous transmission and reflection of reconfigurable intelligent surfaces (STAR-RIS) with SWIPT to maximize spectrum efficiency and reduce overall system energy consumption. This method addresses the considerable energy demands inherent in SWIPT systems by focusing on reducing the power output from the base station (BS) while meeting key constraints: the communication rate for information receivers (IRs) and minimum energy levels for energy receivers (ERs). Given complex interactions between variables, the solution involves an alternating iterative optimization process. In the first stage of this approach, the passive beamforming variables are kept constant, enabling the use of semi-definite relaxation (SDR) and successive convex approximation (SCA) algorithms to optimize active beamforming variables. In the next stage, with active beamforming variables fixed, penalty-based algorithms are applied to fine-tune the passive beamforming variables. This iterative process continues, alternating between active and passive beamforming optimization, until the system converges on a stable solution. The simulation results indicated that the proposed system configuration, which leverages active STAR-RIS, achieves lower energy consumption and demonstrates improved performance compared to configurations utilizing passive RIS, active RIS, and passive STAR-RIS. This evidence suggests that the proposed approach can significantly contribute to advancing energy efficiency in 6G systems.

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Zhao, Ke, Zhiqun Song, Yong Li, Xingjian Li, Lizhe Liu, and Bin Wang. "A Deep Evolution Policy-Based Approach for RIS-Enhanced Communication System." Entropy 26, no. 12 (December 5, 2024): 1056. https://doi.org/10.3390/e26121056.

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This paper investigates the design of active and passive beamforming in a reconfigurable intelligent surface (RIS)-aided multi-user multiple-input single-output (MU-MISO) system with the objective of maximizing the sum rate. We propose a deep evolution policy (DEP)-based algorithm to derive the optimal beamforming strategy by generating multiple agents, each utilizing distinct deep neural networks (DNNs). Additionally, a random subspace selection (RSS) strategy is incorporated to effectively balance exploitation and exploration. The proposed DEP-based algorithm operates without the need for alternating iterations, gradient descent, or backpropagation, enabling simultaneous optimization of both active and passive beamforming. Simulation results indicate that the proposed algorithm can bring significant performance enhancements.

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Zhang, Wenjuan, Honggui Deng, Youzhen Li, Zaoxing Zhu, Chengzuo Peng, and Gang Liu. "Beamforming Optimization for Intelligent Reflecting Surface-Assisted MIMO Systems." Symmetry 14, no. 8 (July 23, 2022): 1510. http://dx.doi.org/10.3390/sym14081510.

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To improve the spectral efficiency of symmetry-based intelligent reconfigurable surface (IRS)-assisted MIMO communication systems, this paper investigates the joint precoding and passive beamforming optimization problem for millimeter-wave point-to-point MIMO systems under both ideal and practical IRS phase shifts. For the ideal IRS phase shifts setup, we derive a simplified approximate spectral efficiency expression based on Jensen’s inequality and propose a minimum mean square error (MMSE)-based algorithm to transform the simplified non-convex problem into a solvable convex function. For the practical IRS phase shifts setup, we propose a multi-start stepwise optimization algorithm to obtain the passive beamforming by stepwise iterative search. Finally, with the above-obtained passive beamforming, the optimal precoding is derived by performing the singular value decomposition (SVD) on the effective channel and water-filling power allocation. The simulation results verify our performance analysis and demonstrate that spectral efficiency can be effectively improved compared to various benchmark schemes.

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Liu, Shijing, Fusheng Gong, Yuebo Li, and Xiangbo Sun. "Kalman filtering used for passive synthetic aperture." Journal of Physics: Conference Series 2756, no. 1 (May 1, 2024): 012013. http://dx.doi.org/10.1088/1742-6596/2756/1/012013.

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Abstract In practice, beamforming-based bearing estimators typically fail to account for the impact of environmental factors on the estimating results, resulting in the so-called mismatch problem. To deal with this issue, this paper reconstructs the bearing estimation as a Kalman filter problem, which emphasizes the role of physical models in underwater acoustic signal processing. Since passive synthetic aperture (PSA) is a spatial process including the temporal evolution of a moving array, it fits a Kalman filtering structure. Kalman filter is applied directly to a lake-test dataset collected by an autonomous underwater vehicle (AUV) shell-mounted array, and the experimental findings demonstrate that the bearing estimation results’ variation is significantly decreased than the conventional beamforming (CBF).

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Qian, Yuyan, Honggui Deng, Aimin Guo, Haoqi Xiao, Chengzuo Peng, and Yinhao Zhang. "Beamforming Design for Cooperative Intelligent Reflecting Surface-Assisted mmWave Communication." Sensors 22, no. 16 (August 18, 2022): 6214. http://dx.doi.org/10.3390/s22166214.

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In order to investigate the effect of cooperative Intelligent Reflecting Surface (IRS) in improving spectral efficiency, this paper explores the joint design of active and passive beamforming based on a double IRS-assisted model. First, considering the maximum power constraint of the active vector and the unit modulus constraint of the cooperative passive vector, we establish the non-linear and non-convex optimization problem of multi-user maximization weighted sum rate (WSR). Then, we propose an alternating optimization (AO) algorithm to design the active vector and the cooperative passive vector based on fractional programming (FP) and successive convex approximations (SCA). In addition, we conduct a study on the optimization of the passive reflection vector under discrete phase shift. The simulation results show that the proposed beamforming scheme of double IRS-assisted model performs better than the conventional single IRS-assisted model.

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Somasundaram, Samuel D. "Wideband Robust Capon Beamforming for Passive Sonar." IEEE Journal of Oceanic Engineering 38, no. 2 (April 2013): 308–22. http://dx.doi.org/10.1109/joe.2012.2223560.

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Abadi, Shima H., Kevin J. Haworth, Karla P. Mercado-Shekhar, and David R. Dowling. "Frequency-sum beamforming for passive cavitation imaging." Journal of the Acoustical Society of America 144, no. 1 (July 2018): 198–209. http://dx.doi.org/10.1121/1.5045328.

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11

Huang, Ke-Wen, and Hui-Ming Wang. "Passive Beamforming for IRS Aided Wireless Networks." IEEE Wireless Communications Letters 9, no. 12 (December 2020): 2035–39. http://dx.doi.org/10.1109/lwc.2020.3011596.

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12

Fromenteze, Thomas, Cyril Decroze, David Carsenat, Aurelian Crunteanu, Matthieu Chatras, and Damien Passerieux. "Passive Beamforming Using Surface Acoustic Wave Filters." IEEE Antennas and Wireless Propagation Letters 14 (2015): 76–79. http://dx.doi.org/10.1109/lawp.2014.2354838.

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Fromenteze, Thomas, Ettien Kpre, David Carsenat, and Cyril Decroze. "CLEAN DECONVOLUTION APPLIED TO PASSIVE COMPRESSED BEAMFORMING." Progress In Electromagnetics Research C 56 (2015): 163–72. http://dx.doi.org/10.2528/pierc15011804.

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Núñez-Ortuño, José M., José P. González-Coma, Rubén Nocelo López, Francisco Troncoso-Pastoriza, and María Álvarez-Hernández. "Beamforming Techniques for Passive Radar: An Overview." Sensors 23, no. 7 (March 24, 2023): 3435. http://dx.doi.org/10.3390/s23073435.

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Passive radar is an interesting approach in the context of non-cooperative target detection. Because the signal source takes advantage of the so-called illuminator of opportunity (IoO), the deployed system is silent, allowing the operator cheap, portable, and practically undetectable deployments. These systems match perfectly with the use of antenna arrays to take advantage of the additional gains provided by the coherent combination of the signals received at each element. To obtain these benefits, linear processing methods are required to enhance the system’s performance. In this work, we summarize the main beamforming methods in the literature to provide a clear picture of the current state of the art. Next, we perform an analysis of the benefits and drawbacks and explore the chance of increasing the number of antenna elements. Finally, we identify the major challenges to be addressed by researchers in the future.

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Droszcz, Aleksander, Konrad Jędrzejewski, Julia Kłos, Krzysztof Kulpa, and Mariusz Pożoga. "Beamforming of LOFAR Radio-Telescope for Passive Radiolocation Purposes." Remote Sensing 13, no. 4 (February 23, 2021): 810. http://dx.doi.org/10.3390/rs13040810.

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This paper presents the results of investigations on the beamforming of a low-frequency radio-telescope LOFAR which can be used as a receiver in passive coherent location (PCL) radars for aerial and space object detection and tracking. The use of a LOFAR radio-telescope for the passive tracking of space objects can be a highly cost-effective solution due to the fact that most of the necessary equipment needed for passive radiolocation already exists in the form of LOFAR stations. The capability of the radiolocation of planes by a single LOFAR station in Borowiec is considered to be ‘proof of concept’ for future research focused on the localization of space objects. Beam patterns of single sets of LOFAR antennas (known as tiles), as well as for the entire LOFAR station, are presented and thoroughly discussed in the paper. Issues related to grating lobes in LOFAR beam patterns are also highlighted. A beamforming algorithm used for passive radiolocation purposes, exploiting data collected by a LOFAR station, is also discussed. The results of preliminary experiments carried out with real signals collected by the LOFAR station in Borowiec, Poland confirm that the appropriate beamforming can significantly increase the radar’s detection range, as well as the detection’s certainty.

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Rosado-Sanz, Javier, María Pilar Jarabo-Amores, David De la Mata-Moya, and Nerea Rey-Maestre. "Adaptive Beamforming Approaches to Improve Passive Radar Performance in Sea and Wind Farms’ Clutter." Sensors 22, no. 18 (September 10, 2022): 6865. http://dx.doi.org/10.3390/s22186865.

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This article presents the problem of passive radar vessel detection in a real coastal scenario in the presence of sea and wind farms’ clutter, which are characterised by high spatial and time variability due to the influence of weather conditions. Deterministic and adaptive beamforming techniques are proposed and evaluated using real data. Key points such as interference localisation and characterisation are tackled in the passive bistatic scenario with omnidirectional illuminators that critically increase the area of potential clutter sources to areas far from the surveillance area. Adaptive beamforming approaches provide significant Signal-to-Interference improvements and important radar coverage improvements. In the presented case study, an aerial target is detected 28 km far from the passive radar receiver, fulfilling highly demanding performance requirements.

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Huang, Ruihua, Shiqiang Suo, Xin Su, and Wenlong Sun. "Distributed Joint Beamforming for RIS-assisted Cell-Free MIMO with Discrete Phase Shifts." Journal of Physics: Conference Series 2829, no. 1 (September 1, 2024): 012011. http://dx.doi.org/10.1088/1742-6596/2829/1/012011.

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Abstract Both reconfiurable intelligent surface (RIS) and cell-free multiple-input multiple-output (CF-MIMO) system are holding promise to become the predominant research direction in 6G networks. This paper studies the problem of weighted sum-rate maximization(WSR) in RIS-assisted CF-MIMO networks with discrete phase shifts. We utilize alternating optimization (AO) to iteratively calculate active and passive beamforming. At access points (APs) side, we employ a distributed algorithm to design the active beamforming, leveraging information interact among APs without centralized designing at central processing unit(CPU). Facing the constraint of discrete phase shift in RIS, we adopt semidefinite relaxation(SDR) projection and proximal gradient descent(PGD) to design the passive beamforming respectively. Simulation results indicate that our proposed algorithms achieve performance comparable to the distributed framework with continuous phase shift while reducing the computational time.

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Gao, Chuanzhe, Shidang Li, Mingsheng Wei, Siyi Duan, and Jinsong Xu. "A Fair Energy Allocation Algorithm for IRS-Assisted Cognitive MISO Wireless-Powered Networks." Information 15, no. 1 (January 16, 2024): 49. http://dx.doi.org/10.3390/info15010049.

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With the rapid development of wireless communication networks and Internet of Things technology (IoT), higher requirements have been put forward for spectrum resource utilization and system performance. In order to further improve the utilization of spectrum resources and system performance, this paper proposes an intelligent reflecting surface (IRS)-assisted fair energy allocation algorithm for cognitive multiple-input single-output (MISO) wireless-powered networks. The goal of this paper is to maximize the minimum energy receiving power in the energy receiver, which is constrained by the signal-to-interference-plus-noise ratio (SINR) threshold of the information receiver in the secondary network, the maximum transmission power at the cognitive base station (CBS), and the interference power threshold of the secondary network on the main network. Due to the coupling between variables, this paper uses iterative optimization algorithms to optimize and solve different variables. That is, when solving the active beamforming variables, the passive beamforming variables are fixed; then, the obtained active beamforming variables are fixed, and the passive beamforming variables are solved. Through continuous iterative optimization, the system converges. The simulation results have verified the effectiveness of the proposed algorithm.

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Lanza di Scalea, Francesco, Chengyang Huang, and Ali Hosseinzadeh. "Ultrasparse ultrasonic synthetic aperture beamforming via passive sensing." Journal of the Acoustical Society of America 155, no. 3_Supplement (March 1, 2024): A101. http://dx.doi.org/10.1121/10.0026949.

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This presentation will describe the implementation of a passive ultrasonic sensing technique to achieve ultrasparse-transmission Synthetic Aperture Focusing (SAF) with Full Matrix Capture (FMC) capabilities. SAF ultrasonic arrays with sparse transmissions have been employed in both medical and industrial NDT imaging to increase imaging speed and simplify multiplexer hardware by reducing the number of high-voltage output channels, at the expense of a reduced beamforming matrix. A technique based on passive reconstruction of the ultrasonic Impulse Response Function (IRF) between two receivers will be demonstrated to create a “virtual” FMC capture while keeping a minimum number of physical transmitters, hence an ultrasparse-transmit array with full synthetic focusing capabilities. Several key steps of this passive beamforming approach will be discussed from both a theoretical and an experimental standpoint. The technique will be demonstrated for the imaging of drilled holes in an aluminum block using a linear, 64-element transducer array and only 1–4 physical transmitters. While the results presented have direct application to NDT imaging of solids, many of the aspects can be potentially applied to ultrafast imaging in the medical field, as well as to seismic interferometry for the health monitoring of civil structures.

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Chen, Jinsong, Kai Wu, Jinping Niu, and Yanyan Li. "Joint Active and Passive Beamforming in RIS-Assisted Secure ISAC Systems." Sensors 24, no. 1 (January 3, 2024): 289. http://dx.doi.org/10.3390/s24010289.

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This paper investigates joint beamforming in a secure integrated sensing and communications (ISAC) system assisted by reconfigurable intelligent surfaces (RIS). The system communicates with legitimate downlink users, detecting a potential target, which is a potential eavesdropper attempting to intercept the downlink communication information from the base station (BS) to legitimate users. To enhance the physical-layer secrecy of the system, we design and introduce interference signals at the BS to disrupt eavesdroppers’ attempts to intercept legitimate communication information. The BS simultaneously transmits communication and interference signals, both utilized for communication and sensing to guarantee the sensing and communication quality. By jointly optimizing the BS active beamformer and the RIS passive beamforming matrix, we aim to maximize the achievable secrecy rate and radiation power of the system. We develop an effective scheme to find the active beamforming matrix through fractional programming (FP) and semi-definite programming (SDP) techniques and obtain the RIS phase shift matrix via a local search technique. Simulation results validate the effectiveness of the proposed methods in enhancing communication and sensing performance. Additionally, the results demonstrate the effectiveness of introducing the interference signals and RIS in enhancing the physical-layer secrecy of the ISAC system.

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AL-Shaeli, Intisar, Lsmail Sharhan Hburi, and Ammar A. Majeed. "Reconfigurable intelligent surface passive beamforming enhancement using unsupervised learning." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (February 1, 2023): 493. http://dx.doi.org/10.11591/ijece.v13i1.pp493-501.

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Reconfigurable intelligent surfaces (RIS) is a wireless technology that has the potential to improve cellular communication systems significantly. This paper considers enhancing the RIS beamforming in a RIS-aided multiuser multi-input multi-output (MIMO) system to enhance user throughput in cellular networks. The study offers an unsupervised/deep neural network (U/DNN) that simultaneously optimizes the intelligent surface beamforming with less complexity to overcome the non-convex sum-rate problem difficulty. The numerical outcomes comparing the suggested approach to the near-optimal iterative semi-definite programming strategy indicate that the proposed method retains most performance (more than 95% of optimal throughput value when the number of antennas is 4 and RIS’s elements are 30) while drastically reducing system computing complexity.

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Somasundaram, Samuel D., and Nigel H. Parsons. "Evaluation of Robust Capon Beamforming for Passive Sonar." IEEE Journal of Oceanic Engineering 36, no. 4 (October 2011): 686–95. http://dx.doi.org/10.1109/joe.2011.2167374.

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23

Carsenat, D., and C. Decroze. "UWB Antennas Beamforming Using Passive Time-Reversal Device." IEEE Antennas and Wireless Propagation Letters 11 (2012): 779–82. http://dx.doi.org/10.1109/lawp.2012.2207872.

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24

Abadi, Shima, Kevin J. Haworth, Karla P. Mercado, and David R. Dowling. "Using frequency-sum beamforming in passive cavitation imaging." Journal of the Acoustical Society of America 141, no. 5 (May 2017): 3613. http://dx.doi.org/10.1121/1.4987745.

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Nor, Ahmed M., Octavian Fratu, and Simona Halunga. "Fingerprint Based Codebook for RIS Passive Beamforming Training." Applied Sciences 13, no. 11 (June 3, 2023): 6809. http://dx.doi.org/10.3390/app13116809.

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In this article, we propose a new RIS passive beamforming scheme in two main stages. First, a fingerprint-based codebook (FP-CB) design phase occurs, where the area of interest is divided into a number of points and the optimal reflection patterns (RPs) corresponding to these points are determined and stored alongside the coordinates of these points in the codebook database (DB). Second, there is the searching and learning online stage, in which, based on the receiver (RX) and FP points’ locations, the system determines a group of candidate RPs. Then, it just searches through them instead of examining the entire CB RPs to select the best RP that can be used for configuring RIS during the data transmission period. The proposed mechanism proves that designing a positioning information-based CB can highly reduce the system overhead computational complexity and enhance performance comparable to the conventional CB-based scheme and the full channel estimation (CE)-based scheme. For example, selecting only 10 candidate RPs from the FP-CB can obtain a better effective achievable rate than a CE-based scheme in a rapidly changing channel.

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Wang, Yujie, Cheng Chi, Yu Li, Donghao Ju, and Haining Huang. "Passive Array-Invariant-Based Localization for a Small Horizontal Array Using Two-Dimensional Deconvolution." Applied Sciences 12, no. 18 (September 18, 2022): 9356. http://dx.doi.org/10.3390/app12189356.

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Recently, the array-invariant method was proposed to passively localize sources of opportunity in shallow water. It exploits multiple arrivals which are different in terms of beam angle and travel time. Conventional plane-wave beamforming in the existing array-invariant method is used to obtain beam-time migration. The resolution capability of conventional plane-wave beamforming is determined by array aperture, which, however, limits the localization accuracy of the existing array-invariant method. To improve the localization accuracy, this study proposes the use of two-dimensional (2D) deconvolution to obtain a better beam-time migration than in conventional plane-wave beamforming. Our simulation with a small horizontal array showed that the range estimation error of the proposed array-invariant method based on 2D deconvolution was only one-third of that of the existing method. The experiment also demonstrated the validity of our proposed method.

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Jiang, Fuchun, Weiming Lin, Hongyi Zhang, Xinhua Lin, and Chenwei Feng. "Design of a Reconfigurable Intelligent Surface Algorithm Based on Multiple-Input Multiple-Output." Traitement du Signal 39, no. 6 (December 31, 2022): 1943–50. http://dx.doi.org/10.18280/ts.390606.

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Reconfigurable Intelligent Surface (RIS) can improve the security of the physical layer of wireless communication by adjusting the phase of the reflective unit. After analyzing the common theoretical models and potential problems, this study proposes an alternative iterative model based on multiple input multiple output (MIMO), and designs the transmitter, channel and receiver. In addition, passive beamforming precoding matrix of RIS was jointly optimized, and the Lagrangian dual relaxation (LDR) was adopted to decouple the nonconvex problem. After that, the active and passive beamforming matrices were subjected to iterative calculation, and the beamforming was optimized through cyclic programming at the base station (BS). In addition, the high convergence of the proposed algorithm was proved by MATLAB simulation. The results of simulation demonstrate that the joint precoding framework algorithm can maximize the weighted sum rate (WSR), which in turn demonstrates the feasibility of our method. Finally, the authors analyzed the strong applicability of the RIS technology in complex wireless networks with different volatility, revealing the possibility of future development.

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Joshi, Arnav, and Jean-Pierre Hickey. "Deep Learning-Based Low-Frequency Passive Acoustic Source Localization." Applied Sciences 14, no. 21 (October 29, 2024): 9893. http://dx.doi.org/10.3390/app14219893.

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This paper develops benchmark cases for low- and very-low-frequency passive acoustic source localization (ASL) using synthetic data. These cases can be potentially applied to the detection of turbulence-generated low-frequency acoustic emissions in the atmosphere. A deep learning approach is used as an alternative to conventional beamforming, which performs poorly under these conditions. The cases, which include two- and three-dimensional ASL, use a shallow and inexpensive convolutional neural network (CNN) with an appropriate input feature to optimize the source localization. CNNs are trained on a limited dataset to highlight the computational tractability and viability of the low-frequency ASL approach. Despite the modest training sets and computational expense, detection accuracies of at least 80% and far superior performance compared with beamforming are achieved—a result that can be improved with more data, training, and deeper networks. These benchmark cases offer well-defined and repeatable representative problems for comparison and further development of deep learning-based low-frequency ASL.

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Yudichak, T. W., and Minh Le. "Cued beamforming of passive arrays in the context of active-passive data fusion." Journal of the Acoustical Society of America 122, no. 5 (2007): 3073. http://dx.doi.org/10.1121/1.2942973.

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KIM, KEONWOOK, and ALAN D. GEORGE. "PARALLEL SUBSPACE PROJECTION BEAMFORMING FOR AUTONOMOUS, PASSIVE SONAR SIGNAL PROCESSING." Journal of Computational Acoustics 11, no. 01 (March 2003): 55–74. http://dx.doi.org/10.1142/s0218396x0300181x.

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Adaptive techniques can be applied to improve performance of a beamformer in a cluttered environment. The sequential implementation of an adaptive beamformer, for many sensors and over a wide band of frequencies, presents a serious computational challenge. By coupling each transducer node with a microprocessor, in-situ parallel processing applied to an adaptive beamformer on a distributed system can glean advantages in execution speed, fault tolerance, scalability, and cost. In this paper, parallel algorithms for Subspace Projection Beamforming (SPB), using QR decomposition on distributed systems, are introduced for in-situ signal processing. Performance results from parallel and sequential algorithms are presented using a distributed system testbed comprised of a cluster of computers connected by a network. The execution times, parallel efficiencies, and memory requirements of each parallel algorithm are presented and analyzed. The results of these analyses demonstrate that parallel in-situ processing holds the potential to meet the needs of future advanced beamforming algorithms in a scalable fashion.

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Liu, Ya, Jianghai Xia, Feng Cheng, Chaoqiang Xi, Chao Shen, and Changjiang Zhou. "Pseudo-linear-array analysis of passive surface waves based on beamforming." Geophysical Journal International 221, no. 1 (January 11, 2020): 640–50. http://dx.doi.org/10.1093/gji/ggaa024.

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SUMMARY Linear arrays are usually deployed for passive surface-wave investigations because of their high efficiency and convenience. In populated urban areas, it is almost impossible to set up a 2-D array in terms of the restriction from the existing infrastructures. The limited azimuthal coverage, however, lacks the ability to attenuate velocity overestimation caused by directional noise sources. We came up with a novel idea to compensate the azimuthal coverage by adding two more offline receivers to a conventional linear array, which is called pseudo-linear-array analysis of passive surface waves (PLAS). We used a beamforming algorithm to capture noise sources distribution and extract accurate dispersion curves. We used array response function to explain the superiority of the pseudo-linear array over the linear array and present the basic workflow of PLAS. Synthetic tests and field examples demonstrated the feasibility of PLAS to measure unbiased dispersion image. Comparison with mostly used passive surface wave methods (refraction microtremor, multichannel analysis of passive surface waves, spatial autocorrelation method, frequency–wavenumber analysis) suggested that PLAS can serve as an alternative passive surface wave method, especially in urban areas with restricted land accessibility and short-time acquisition demands.

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Li, Jianghui, Paul R. White, Jonathan M. Bull, Timothy G. Leighton, Ben Roche, and John W. Davis. "Passive acoustic localisation of undersea gas seeps using beamforming." International Journal of Greenhouse Gas Control 108 (June 2021): 103316. http://dx.doi.org/10.1016/j.ijggc.2021.103316.

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Wang, Fangzhou, Hongbin Li, and Jun Fang. "Joint Active and Passive Beamforming for IRS-Assisted Radar." IEEE Signal Processing Letters 29 (2022): 349–53. http://dx.doi.org/10.1109/lsp.2021.3134899.

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Cai, Chang, Xiaojun Yuan, Wenjing Yan, Zhouyang Huang, Ying-Chang Liang, and Wei Zhang. "Hierarchical Passive Beamforming for Reconfigurable Intelligent Surface Aided Communications." IEEE Wireless Communications Letters 10, no. 9 (September 2021): 1909–13. http://dx.doi.org/10.1109/lwc.2021.3085497.

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Yan, Wenjing, Xiaojun Yuan, and Xiaoyan Kuai. "Passive Beamforming and Information Transfer via Large Intelligent Surface." IEEE Wireless Communications Letters 9, no. 4 (April 2020): 533–37. http://dx.doi.org/10.1109/lwc.2019.2961670.

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Lamothe, Nathalie, Diana Andrés, Alicia Carrión, Francisco Camarena, José A. Pineda-Pardo, and Noé Jiménez. "Monitoring holograms for therapeutic ultrasound using passive cavitation beamforming." Applied Acoustics 224 (September 2024): 110144. http://dx.doi.org/10.1016/j.apacoust.2024.110144.

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Myung, Jungho, Keunyoung Kim, and Taehong Kim. "Threshold Secret Sharing Transmission against Passive Eavesdropping in MIMO Wireless Networks." Wireless Communications and Mobile Computing 2018 (October 22, 2018): 1–7. http://dx.doi.org/10.1155/2018/4143061.

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We propose a threshold secret sharing scheme for secure communications in multiple input and multiple output wireless networks. In the proposed scheme, the base station divides the secret data into Nmin parts using a polynomial of degree T-1 (T≤Nmin) and transmits the divided data to the legitimate user by beamforming with multiple spatial dimensions. Then, at the user, the secret data can be reconstructed with a sufficient number (≥T) of divided parts by using the Lagrange interpolating polynomial. However, it is difficult for the eavesdropper to correctly estimate the T parts due to the difference between the main channel with beamforming and the eavesdropping channel in the physical layer, which results in the failure of secret data reconstruction. The numerical results show that the eavesdropping probability of the proposed scheme is lower than those of conventional schemes. Moreover, we analyze the symbol-error-rate and show that the theoretical result is well aligned with simulation results.

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Kang, Jae-Mo, and Dong-Woo Lim. "Joint channel training and passive beamforming design for intelligent reflecting surface-aided LoRa systems." AIMS Mathematics 9, no. 5 (2024): 11423–31. http://dx.doi.org/10.3934/math.2024560.

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<abstract>In order to examine the potential and synergetic aspects of intelligent reflecting surface (IRS) techniques for Internet-of-Things (IoT), we study an IRS-aided Long Range (LoRa) system in this paper. Specifically, to facilitate the acquisition of accurate channel state information (CSI) for effective reflection of LoRa signals, we first propose an optimal training design for the least squares channel estimation with LoRa modulation, and then, by utilizing the acquired CSI, we develop a high-performing passive beamforming scheme based on a signal-to-ratio (SNR) criterion. Numerical results show that the proposed training design considerably outperforms the baseline schemes, and the proposed passive beamforming design results in a significant improvement in performance over that of the conventional LoRa system, thereby demonstrating the feasibility of extending coverage areas of LoRa systems with the aid of IRS.</abstract>

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Ganti, Anil, Michael Martinez, Granger Hickman, and Jeffrey Krolik. "A wavefront adaptive sensing beamformer for ocean acoustic waveguides." Journal of the Acoustical Society of America 154, no. 4 (October 1, 2023): 2398–409. http://dx.doi.org/10.1121/10.0021310.

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This paper addresses robust adaptive beamforming for passive sonar in uncertain, shallow-water environments. Conventional beamforming is still common in passive sonar because adaptive beamformers suffer from signal mismatch in complex multipath environments. Existing approaches to robust adaptive beamforming try to model and account for the uncertainty in the beamformer's hypothesized signal subspace by using additional linear or quadratic constraints. Doing so, however, reduces the adaptivity of the beamformer and is prone to insufficiently suppressing interference. Instead, this paper uses blind source separation methods to adaptively estimate the complex spatial wavefronts of both targets and interference without requiring detailed physical modeling of the channel. By exploiting the different temporal spectra and/or frequency-selective multipath fading of targets and interference, this approach constructs a “signal-free” covariance matrix without imposing directional gain constraints. In doing so, the wavefront adaptive sensing (WAS) beamformer is able to separate targets from strong interference that is within the conventional beam width of the target. Simulation results in a realistic shallow-water channel are presented as well as results using the SWellEx96 S59 data with an injected target to show that the proposed WAS beamformer outperforms conventional and minimum variance adaptive beamformers in a shallow-water scenario.

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Zhao, Kangchun, Yijie Mao, and Yuanming Shi. "Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces Empowered Cooperative Rate Splitting with User Relaying." Entropy 26, no. 12 (November 26, 2024): 1019. http://dx.doi.org/10.3390/e26121019.

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In this work, we unveil the advantages of synergizing cooperative rate splitting (CRS) with user relaying and simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR RIS). Specifically, we propose a novel STAR RIS-assisted CRS transmission framework, featuring six unique transmission modes that leverage various combinations of the relaying protocols (including full duplex-FD and half duplex-HD) and the STAR RIS configuration protocols (including energy splitting-ES, mode switching-MS, and time splitting-TS). With the objective of maximizing the minimum user rate, we then propose a unified successive convex approximation (SCA)-based alternative optimization (AO) algorithm to jointly optimize the transmit active beamforming, common rate allocation, STAR RIS passive beamforming, as well as time allocation (for HD or TS protocols) subject to the transmit power constraint at the base station (BS) and the law of energy conservation at the STAR RIS. To alleviate the computational burden, we further propose a low-complexity algorithm that incorporates a closed-form passive beamforming design. Numerical results show that our proposed framework significantly enhances user fairness compared with conventional CRS schemes without STAR RIS or other STAR RIS-empowered multiple access schemes. Moreover, the proposed low-complexity algorithm dramatically reduces the computational complexity while achieving very close performance to the AO method.

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Wang, Dawei, Yang Zhao, Yixin He, Xiao Tang, Lixin Li, Ruonan Zhang, and Daosen Zhai. "Passive Beamforming and Trajectory Optimization for Reconfigurable Intelligent Surface-Assisted UAV Secure Communication." Remote Sensing 13, no. 21 (October 25, 2021): 4286. http://dx.doi.org/10.3390/rs13214286.

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Unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) methods are promising techniques for improving the energy and spectrum efficiency of Fifth Generation/Beyond Fifth Generation (5G/B5G) networks. In order to take advantage of both techniques, we propose an RIS-assisted UAV secure communication scheme, where an UAV is equipped with RIS to facilitate secure transmission. To maximize the average secrecy rate, we jointly optimize the beamforming power, reflect phase shift, and UAV’s trajectory. For this non-convex problem, we decompose it into the power beamforming problem, the phase shift optimization problem, and the UAV’s trajectory design problem, and proposed an efficient iterative algorithm to solve the problem. The numerical results verify the superiority of the proposed scheme that can improve the average secure transmission rate by about 20% compared to that of Eavesdropping elimination methods.

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Zhang, Yu, Bingpu Wang, Xiaobo Rui, Jin Zhang, Hao Feng, and Jian Li. "A continuous underwater bubble localization method using passive acoustic array beamforming." AIP Advances 12, no. 5 (May 1, 2022): 055004. http://dx.doi.org/10.1063/5.0083892.

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The bubble is an effective carrier of underwater gas leakage detection, and its rapid localization is of great significance. In this paper, a continuous underwater bubble localization method using passive acoustic array beamforming is proposed. A specific array of hydrophones was constructed to capture the bubble acoustic signal. The signal of finite length is obtained by introducing the time window. Then, the time delay compensation is carried out according to the positions of the hydrophones in the array to estimate the direction of arrival. The influence of shape, number, and aperture of the hydrophone array on the algorithm performance is studied by simulation. Moreover, the experiment was carried out in a cuboid transparent tempered glass water tank in the laboratory, and a field programmable gate array is used as the core control unit of the data processing system to complete the signal acquisition and the algorithm execution. The localization results show that the passive acoustic cross array beamforming algorithm can accurately and stably estimate the leakage direction at different positions.

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Zhang, Hui, Qiming Jia, Meikun Li, Jingjing Wang, and Yuxin Song. "Passive Beamforming Design of IRS-Assisted MIMO Systems Based on Deep Learning." Sensors 23, no. 16 (August 14, 2023): 7164. http://dx.doi.org/10.3390/s23167164.

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In the intelligent reflecting surface (IRS)-assisted MIMO systems, optimizing the passive beamforming of the IRS to maximize spectral efficiency is crucial. However, due to the unit-modulus constraint of the IRS, the design of an optimal passive beamforming solution becomes a challenging task. The feature input of existing schemes often neglects to exploit channel state information (CSI), and all input data are treated equally in the network, which cannot effectively pay attention to the key information and features in the input. Also, these schemes usually have high complexity and computational cost. To address these issues, an effective three-channel data input structure is utilized, and an attention mechanism-assisted unsupervised learning scheme is proposed on this basis, which can better exploit CSI. It can also better exploit CSI by increasing the weight of key information in the input data to enhance the expression and generalization ability of the network. The simulation results show that compared with the existing schemes, the proposed scheme can effectively improve the spectrum efficiency, reduce the computational complexity, and converge quickly.

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Kang, Tae-Su, DongGwan Kim, and Chang-Ho Choi. "Robust Focused Adaptive Beamforming for Passive Sonar in Doppler Environments." Journal of the Institute of Electronics and Information Engineers 56, no. 11 (November 30, 2019): 74–80. http://dx.doi.org/10.5573/ieie.2019.56.11.74.

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Feng, Chenghao, Wenqian Shen, Xinyu Gao, and Jianping An. "Passive beamforming design for intelligent reflecting surface assisted MIMO systems." China Communications 18, no. 3 (March 2021): 18–28. http://dx.doi.org/10.23919/jcc.2021.03.002.

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Zheng, Beixiong, Changsheng You, and Rui Zhang. "Double-IRS Assisted Multi-User MIMO: Cooperative Passive Beamforming Design." IEEE Transactions on Wireless Communications 20, no. 7 (July 2021): 4513–26. http://dx.doi.org/10.1109/twc.2021.3059945.

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He, Zhenyao, Hong Shen, Wei Xu, and Chunming Zhao. "Low-Cost Passive Beamforming for RIS-Aided Wideband OFDM Systems." IEEE Wireless Communications Letters 11, no. 2 (February 2022): 318–22. http://dx.doi.org/10.1109/lwc.2021.3126852.

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Chen, Peng, Long Zuo, and Wei Wang. "Adaptive Beamforming for Passive Synthetic Aperture with Uncertain Curvilinear Trajectory." Remote Sensing 13, no. 13 (June 30, 2021): 2562. http://dx.doi.org/10.3390/rs13132562.

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Recently, numerous reconstruction-based adaptive beamformers have been proposed, which can improve the quality of imaging or localization in the application of passive synthetic aperture (PSA) sensing. However, when the trajectory is curvilinear, existing beamformers may not be robust enough to suppress interferences efficiently. To overcome the model mismatch of unknown curvilinear trajectory, this paper presents an adaptive beamforming algorithm by reconstructing the interference-plus-noise covariance matrix (INCM). Using the idea of signal subspace fitting, we construct a joint optimization problem, where the unknown directions of arrival (DOAs) and array shape parameters are coupled together. To tackle this problem, we develop a hybrid optimization method by combining the genetic algorithm and difference-based quasi-Newton method. Then, a set of non-orthogonal bases for signal subspace is estimated with an acceptable computational complexity. Instead of reconstructing the covariance matrix by integrating the spatial spectrum over interference angular sector, we extract the desired signal covariance matrix (DSCM) directly from signal subspace, and then the INCM is reconstructed by eliminating DSCM from the sample covariance matrix (SCM). Numerical simulations demonstrate the robustness of the proposed beamformer in the case of signal direction error, local scattering and random curvilinear trajectory.

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Zheng, Beixiong, and Rui Zhang. "IRS Meets Relaying: Joint Resource Allocation and Passive Beamforming Optimization." IEEE Wireless Communications Letters 10, no. 9 (September 2021): 2080–84. http://dx.doi.org/10.1109/lwc.2021.3092222.

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Asaad, Saba, Yifei Wu, Ali Bereyhi, Ralf R. Muller, Rafael F. Schaefer, and H. Vincent Poor. "Secure Active and Passive Beamforming in IRS-Aided MIMO Systems." IEEE Transactions on Information Forensics and Security 17 (2022): 1300–1315. http://dx.doi.org/10.1109/tifs.2022.3159108.

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Journal articles on the topic 'Passive Beamforming'

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