Adaptive broadband beamformer for nonuniform linear array based on second order cone programming

Adaptive broadband beamforraing is a key issue in array applications. The adaptive broadband beamformer with tapped delay line （TDL） structure for nonuniform linear array （NLA） is designed according to the rule of minimizing the beamformer＇s output power while keeping the distortionless response （DR） in the direction of desired signal and keeping the constant beamwidth （CB） with the prescribed sidelobe level over the whole operating band. This kind of beamforming problem can be solved with the interior-point method after being converted to the form of standard second order cone programming （SOCP）. The computer simulations are presented which illustrate the effectiveness of our beamformer.

Dorsal-Ventral Visual Pathways and Object Characteristics:Beamformer Source Analysis of EEG

In performing a gaming task,mental rotation(MR)is one of the important aspects of visuospatial processing.MR involves dorsal-ventral pathways of the brain.Visual objects/models used in computer-games play a crucial role in gaming experience of the users.The visuospatial characteristics of the objects used in the computer-game influence the engagement of dorsal-ventral visual pathways.The current study investigates how the objects’visuospatial characteristics(i.e.,angular disparity and dimensionality)in an MR-based computer-game influence the cortical activities in dorsalventral visual pathways.Both the factors have two levels,angular disparity:convex angle(CA)vs.reflex angle(RA)and dimensionality:2D vs.3D.Sixty healthy adults,aged,18-29 years(M=21.6)were recruited for the study and randomly assigned to four gaming conditions i.e.,15 participants in each group.The multichannel electroencephalogram(EEG)data were recorded from 60 healthy adults while playing the game.The source reconstruction was done for∼3000 sources inside the brain using the Dynamic Imaging of Coherent Sources(DICS)beamforming method forθ1(4-5.75),θ2(5.75-7.5),α1(7.5-9),α2(9-11),α3(11-13),β1(13-17.25),β2(17.25-21.5)Hz frequency sub-bands.The reconstructed neuronal sources were segmented into 68 functionally parcellated brain regions,and the percentage of active sources for each region was computed.Further,the differences across the 68 regions among the four gaming conditions were evaluated using the percentage of active sources.The differences in activation for the dorsal-ventral pathways and some additional brain regions were observed among the four groups.The game with 2D objects and CA showed higher activation than that with 3D objects and RA,respectively.The dorsal pathway was found to be more active in contrast to the ventral pathway.The findings suggest that angular disparity and dimensionality in MR influence the engagement of dorsal-ventral visual pathways in such a way that angular disparity has a greater impact on cortical activation across this region than dimensionality.Also,higher activation for CA as compared to RA irrespective of dimensionality reflects the complexity of spatial information processing under CA.Similarly,greater activation was seen for 2D objects than 3D,indicating difficulty in information processing due to deficient visual features.

A parallel complex divider architecture based on DCD iterations for computing complex division in MVDR beamformer

This paper presents a hardware architecture using mixed pipeline and parallel processing for complex division based on dichotomous coordinate descent(DCD) iterations. The objective of the proposed work is to achieve low-latency and resource optimized complex divider architecture in adaptive weight computation stage of minimum variance distortionless response(MVDR)algorithm. In this work, computation of complex division is modeled as a 2×2 linear equation solution problem and the DCD algorithm allows linear systems of equations to be solved with high degree of computational efficiency. The operations in the existing DCD algorithm are suitably parallel pipelined and the performance is optimized to 2 clock cycles per iteration. To improve the degree of parallelism, a parallel column vector read architecture is devised.The proposed work is implemented on the field programmable gate array(FPGA) platform and the results are compared with state-of-art literature. It concludes that the proposed architecture is suitable for complex division in adaptive weight computation stage of MVDR beamformer. We demonstrate the performance of the proposed architecture for MVDR beamformer employed in medical ultrasound imaging applications.

Implementing Delay Multiply and Sum Beamformer on a Hybrid CPU-GPU Platform for Medical Ultrasound Imaging Using Open MP and CUDA

Anovel beamforming algorithmnamed Delay Multiply and Sum(DMAS),which excels at enhancing the resolution and contrast of ultrasonic image,has recently been proposed.However,there are nested loops in this algorithm,so the calculation complexity is higher compared to the Delay and Sum(DAS)beamformer which is widely used in industry.Thus,we proposed a simple vector-based method to lower its complexity.The key point is to transform the nested loops into several vector operations,which can be efficiently implemented on many parallel platforms,such as Graphics Processing Units(GPUs),and multi-core Central Processing Units(CPUs).Consequently,we considered to implement this algorithm on such a platform.In order to maximize the use of computing power,we use the GPUs andmulti-core CPUs inmixture.The platform used in our test is a low cost Personal Computer(PC),where a GPU and a multi-core CPU are installed.The results show that the hybrid use of a CPU and a GPU can get a significant performance improvement in comparison with using a GPU or using amulti-core CPU alone.The performance of the hybrid system is increased by about 47%–63%compared to a single GPU.When 32 elements are used in receiving,the fame rate basically can reach 30 fps.In the best case,the frame rate can be increased to 40 fps.

High-Performance Beamformer and Low-Complexity Detector for DF-Based Full-Duplex MIMO Relaying Networks

In this paper, we consider a full.duplex multiple.input multiple.output(MIMO) relaying network with the decode.and.forward(DF) protocol. Due to the full.duplex transmissions, the self.interference from the relay transmitter to the relay receiver degrades the system performance. We thus propose an iterative beamforming structure(IBS) to mitigate the self.interference. In this method, the receive beamforming at the relay is optimized to maximize the signal.to.interference.plus.noise.ratio(Max.SINR), while the transmit beamforming at the relay is optimized to maximize the signal.to.leakage.plusnoise.ratio(Max.SLNR). To further improve the performance, the receive and transmit beamforming matrices are optimized between Max.SINR and Max.SLNR in an iterative manner. Furthermore, in the presence of the residual self.interference, a low.complexity whitening.filter(WF) maximum likelihood(ML) detector is proposed. In this detector, a WF is designed to transform a colored interference.plus.noise to a white noise, while the singular value decomposition is used to convert coupled spatial subchannels to parallelindependent ones. From simulations, we find that the proposed IBS performs much better than the existing schemes. Also, the proposed low.complexity detector significantly reduces the complexity of the conventional ML(CML) detector from exponential time(an exponential function of the number of the source transmit antennas) to polynomial one while achieving a slightly better BER performance than the CML due to interference whitening.

Non-Statistical Multi-Beamformer

In this paper, a multiple beamforming technique is presented by using a direct data domain least squares (D3LS) approach. Direct data domain approach is very suitable for real time applications since it utilizes only a single snapshot of data as opposed to statistical approaches where multiple measurements have to be taken and the covariance matrix has to be formed. It is also very effective especially in the case of blinking jammers where the statistical approaches will fail or needs to perform additional tasks to overcome it. It has been previously shown that the D3LS can successfully handle only one or two Signal of Interests (SOI). Here, we have developed a new technique where multiple SOI can be handled simultaneously. Numerical simulations have shown that the new approach can maximize the signals from the direction of the SOI at the same time minimizing the jammers. The new approach can be successfully applied in the satellite communications, Over the Horizon Radars (OTHR) as well as wireless communications to detect or track multiple targets simultaneously.

Design of Fuze Antenna Beamformer Based on DSP

According to the algorithm of the fuze antenna beamforming and the requirement for the realtime performenee, a fuze antenna beamformer based on digital signal processor （DSP） was designed. The program was written in C, and in order to reduce the operation time of DSP, the key part of the matrix operation was written in simple algorithm. The precise and speediness of DSP calculation results were analyzed through Matlab and the Profiling tools in Code Composer Studio （CCS）. The results show that the precise and the speediness both can satisfy the requirement for the fuze antennh beamforming.

A New On-Line/Off-Line Adaptive Antenna Array Beamformer for Tracking the Mobile Targets

An adaptive antenna array system adjusts the main lobe of radiation pattern in the direction of desired signal and points the nulls in the direction of undesired signals or interferers. The essential goal of beamforming is to reduce the complexity of weighting process and to decrease the time needed for adjusting the antenna radiation pattern. In this article a new adaptive weighting algorithm is proposed for both least mean squares (LMS) and constant modulus (CM) algorithms. It is appropriate and applicable for antenna array systems with moving targets and also mobile applications as well as sensor networks. By predicting the relative velocity of source, the next location of the source will be estimated and the array weights will be determined using LMS or CM algorithm before arriving to the new point. For the next time associated to the new sampling point, evaluated weights will be used. Furthermore, by updating these weights between two consecutive times the effects of error propagation will be eliminated. Therefore, in addition to reduction in computational complexity at the time of weight allocation, relatively accurate weight allocation can be obtained. Simulation results of this investigation show that the angular error related to both LMS-based and CM-based algorithms is less than the conventional LMS and CM algorithms at different signal to noise ratios (SNRs). On the other hand, due to considering off-line process, online computational complexity of new algorithms is slightly low with respect to previous ones.

基于聚焦变换解卷积的宽带稳健波束形成

In the field of array signal processing,uniform linear arrays(ULAs)are widely used to detect/separate a weak target and estimate its direction of arrival from interference and noise.Conventional beamforming(CBF)is robust but restricted by a wide mainlobe and high sidelobe level.Covariance-matrix-inversed beamforming techniques,such as the minimum variance distortionless response and multiple signal classification,are sensitive to signal mismatch and data snapshots and exhibit high-resolution performance because of the narrow mainlobe and low sidelobe level.Therefore,compared with the wideband CBF,this study proposes a robust focused-and-deconvolved conventional beamforming(RFD-CBF),utilizing the Richardson–Lucy(R-L)iterative algorithm to deconvolve the focused conventional beam power of a half-wavelength spaced ULA.Then,the focused-and-deconvolved beam power achieves a narrower mainlobe and lower sidelobe level while retaining the robustness of wideband CBF.Moreover,compared with the wideband CBF,RFD-CBF can obtain a higher output signal-to-noise ratio(SNR).Finally,the performance of RFD-CBF is evaluated through numerical simulation and verified by sea trial data processing.

Beam Training and Tracking in mmWave Communication:A Survey

Communicating on millimeter wave(mmWave)bands is ushering in a new epoch of mobile communication which provides the availability of 10 Gbps high data rate transmission.However,mmWave links are easily prone to short transmission range communication because of the serious free space path loss and the blockage by obstacles.To overcome these challenges,highly directional beams are exploited to achieve robust links by hybrid beamforming.Accurately aligning the transmitter and receiver beams,i.e.beam training,is vitally important to high data rate transmission.However,it may cause huge overhead which has negative effects on initial access,handover,and tracking.Besides,the mobility patterns of users are complicated and dynamic,which may cause tracking error and large tracking latency.An efficient beam tracking method has a positive effect on sustaining robust links.This article provides an overview of the beam training and tracking technologies on mmWave bands and reveals the insights for future research in the 6th Generation(6G)mobile network.Especially,some open research problems are proposed to realize fast,accurate,and robust beam training and tracking.We hope that this survey provides guidelines for the researchers in the area of mmWave communications.

Channel-Feedback-Free Transmission for Downlink FD-RAN:A Radio Map Based Complex-Valued Precoding Network Approach

As the demand for high-quality services proliferates,an innovative network architecture,the fully-decoupled RAN(FD-RAN),has emerged for more flexible spectrum resource utilization and lower network costs.However,with the decoupling of uplink base stations and downlink base stations in FDRAN,the traditional transmission mechanism,which relies on real-time channel feedback,is not suitable as the receiver is not able to feedback accurate and timely channel state information to the transmitter.This paper proposes a novel transmission scheme without relying on physical layer channel feedback.Specifically,we design a radio map based complex-valued precoding network(RMCPNet)model,which outputs the base station precoding based on user location.RMCPNet comprises multiple subnets,with each subnet responsible for extracting unique modal features from diverse input modalities.Furthermore,the multimodal embeddings derived from these distinct subnets are integrated within the information fusion layer,culminating in a unified representation.We also develop a specific RMCPNet training algorithm that employs the negative spectral efficiency as the loss function.We evaluate the performance of the proposed scheme on the public DeepMIMO dataset and show that RMCPNet can achieve 16%and 76%performance improvements over the conventional real-valued neural network and statistical codebook approach,respectively.

Cooperative Covert Communication in Multi-Antenna Broadcast Channels

With the gradual popularization of 5G communications,the application of multi-antenna broadcasting technology has become widespread.Therefore,this study aims to investigate the wireless covert communication in the two-user cooperative multi-antenna broadcast channel.We focus on the issue that the deteriorated reliability and undetectability are mainly affected by the transmission power.To tackle this issue,we design a scheme based on beamforming to increase the reliability and undetectability of wireless covert communication in the multi-antenna broadcast channel.We first modeled and analyzed the cooperative multi-antenna broadcasting system,and put forward the target question.Then we use the SCA(successive convex approximation)algorithm to transform the target problem into a series of convex subproblems.Then the convex problems are solved and the covert channel capacity is calculated.In order to verify the effectiveness of the scheme,we conducted simulation verification.The simulation results show that the proposed beamforming scheme can effectively improve the reliability and undetectability of covert communication in multi-antenna broadcast channels.

Anti-Jamming Null Space Projection Beamforming Based on Symbiotic Radio

With the development of information technology,more and more devices are connected to the Internet through wireless communication to complete data interconnection.Due to the broadcast characteristics ofwireless channels,wireless networks have suffered more and more malicious attacks.Physical layer security has received extensive attention from industry and academia.MIMO is considered to be one of the most important technologies related to physical layer security.Through beamforming technology,messages can be transmitted to legitimate users in an offset direction that is as orthogonal as possible to the interference channel to ensure the reception SINR by legitimate users.Combining the symbiotic radio(SR)technology,this paper considers a symbiotic radio antijamming MIMO system equipped with a multi-antenna system at the main base station.In order to avoid the interference signal and improve the SINR of the signal received by the user.The base station is equipped with a uniform rectangular antenna array,and using Null Space Projection(NSP)Beamforming,Intelligent Reflecting Surface(IRS)can assist in changing the beam’s angle.The simulation results show that NSP Beamforming could make a better use of the null space of interference,which can effectively improve the received SINR of users under directional interference,and improve the utilization efficiency of signal energy.

Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics

In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial filtering.If the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation effect.To cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range dimension.The principle is presented,and the validity is proven by simulation results.

Transmit Power Minimization for IRS-Assisted NOMA-UAV Networks

The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction.Motivated by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS.According to their distance to the UAV,the users are divided into the close users and remote users.The UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received power.We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement.However,the problem is non-convex.Therefore,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,respectively.We propose an iterative algorithm to solve the two sub-problems alternatively.Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.

Sum-Rate Maximization in Active RIS-Assisted Multi-Antenna WPCN

In this paper,we propose an active reconfigurable intelligent surface(RIS)enabled hybrid relaying scheme for a multi-antenna wireless powered communication network(WPCN),where the active RIS is employed to assist both wireless energy transfer(WET)from the power station(PS)to energyconstrained users and wireless information transmission(WIT)from users to the receiving station(RS).For further performance enhancement,we propose to employ both transmit beamforming at the PS and receive beamforming at the RS.We formulate a sumrate maximization problem by jointly optimizing the RIS phase shifts and amplitude reflection coefficients for both the WET and the WIT,transmit and receive beamforming vectors,and network resource allocation.To solve this non-convex problem,we propose an efficient alternating optimization algorithm with the linear minimum mean squared error criterion,semidefinite relaxation(SDR)and successive convex approximation techniques.Specifically,the tightness of applying the SDR is proved.Simulation results demonstrate that our proposed scheme with 10 reflecting elements(REs)and 4 antennas can achieve 17.78%and 415.48%performance gains compared to the single-antenna scheme with 10 REs and passive RIS scheme with 100 REs,respectively.

Performance analysis of the mutual coupling effect on Phased Array Feeds

A phased array feed(PAF)is a type of receiving array that places phased array antennas on the focal plane of a radio telescope to expand its field of view and improve observation efficiency.Owing to the mutual coupling effect between elements caused by a tightly arranged feed array,which changes the performance of a PAF,this paper presents a 7×7 rectangular feed array model for a 25 m reflector telescope.By adjusting the element spacings,the performance of a PAF with different spacings is comprehensively analyzed with respect to the mutual coupling effect via performance statistics and comparison.This research aims to provide a reference for the preliminary design of a related PAF.

Cooperative Distributed Beamforming Design for Multi-RIS Aided Cell-Free Systems

Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost problems of both hardware and power consumption.In this paper,we investigate multiple reconfigurable intelligent surfaces(RISs)aided cell-free systems where RISs are introduced to improve spectrum efficiency in an energy-efficient way.To overcome the centralized high complexity and avoid frequent information exchanges,a cooperative distributed beamforming design is proposed to maximize the weighted sum-rate performance.In particular,the alternating optimization method is utilized with the distributed closed-form solution of active beamforming being derived locally at access points,and phase shifts are obtained centrally based on the Riemannian conjugate gradient(RCG)manifold method.Simulation results verify the effectiveness of the proposed design whose performance is comparable to the centralized scheme and show great superiority of the RISs-aided system over the conventional cellular and cell-free system.

Linear beamformer schemes with simple relay selection in MIMO relay networks

This article considers a wireless multi-hop/mesh network where single multi-antenna source-destination pair communicates through a selected relay subset using simple relay selection under the constraint of fixed relay＇s number. Compared with random selection, the simple relay selection can yield certain capacity advantages while linear zero-forcing （ZF） receiver and linear beamformer are considered at the relay. For match-filter （MF） beamformer and amplified-and-forward （AF） beamformer with a fixed number of relays, the capacities are given. Furthermore, we extend the simple selection methods to the relaying scheme with orthogonal-triangular （QR） beamformer and investigate these linear beamformer schemes over spatially correlated multi-input multi-output （MIMO） links for both the backward and forward channel over the two-bop MIMO relay networks.

Analysis of the Influence of Sound Source Position and Electrode Placement on the Stimulation Pattern of the Cochlear Implant under Noise Conditions: Optimization of Auditory Perceptual Effects

Background: Cochlear implants (CI) are widely used to restore hearing in people with severe to profound hearing loss. However, optimizing CI performance, especially in difficult listening environments with background noise, remains a major challenge. Understanding the influence of factors such as sound source position and electrode placement on CI stimulation patterns is critical to improving auditory perception. Methods: In this study, an analysis was conducted to investigate the influence of sound source position and electrode placement on CI stimulation patterns under noisy conditions. For this purpose, a special measurement setup with a CI speech processor-microphone test box was used to simulate realistic listening scenarios and measure CI performance. Results: The results show that the effectiveness of CI noise reduction systems is influenced by factors such as the position of the sound source and electrode placement. In particular, the beamforming ultra zoom mode showed significantly better noise reduction than the omnidirectional mode, especially under real listening conditions. Furthermore, differences in electrode responses indicate individual variability in the CI user experience, highlighting the importance of personalized fitting algorithms. Conclusions: The results demonstrate the importance of considering environmental factors and individual differences when optimizing CI performance. Future research efforts should focus on the development of personalized fitting algorithms and the exploration of innovative strategies, such as the integration of artificial intelligence, to improve CI functionality in different listening environments. This study contributes to our understanding of CI stimulation patterns and lays the foundation for improving auditory perception in CI users.