Performance Of Beamformer Research Articles

An 8-Channel Varactor-Less 28-GHz Front End With 7-Bit Resolution 340° RTPS for 5G RF Beamformers

An 8-way power combined, high gain, very low power varactor-less front end in a 45 nm bulk CMOS process is presented in this brief. The fully digital near-360° seven-bit reflection type phase shifter (RTPS) utilises a novel varactor-less tuning network in a triple resonating load along with negative resistance generators to reduce the insertion loss. A two-stage passive gm boosted CG-CS low noise amplifier (LNA) with series peaking delivers 32dB gain with a very low DC power consumption. The 8:1 lumped quarter wave combiner/splitter utilizes transformer coupling to achieve a post layout efficiency of 67%, with a 2X reduction in area when compared to a spiral inductor-only implementation. Post-layout EM simulations on the RTPS predict a 340° phase shift with insertion loss of 9± 5dB at a very high resolution of 2.8°. The front end yields an overall gain of 21± 5dB, with a worst-case noise figure (NF) of 4.7dB while consuming only 10mW per channel. With an inter channel isolation greater than 22 dB, the amplitude and phase mismatch of the front end are kept within 0.3dB and 3° respectively. The impact of module and PCB non-idealities on the beamformer performance have also been highlighted with support from initial system level simulations. To the best of the authors’ knowledge, this is the first implementation of a fully digital near-360° RF beamforming front end with simultaneous high gain and phase resolution.

Robust Adaptive Beamforming via Simplified Interference Power Estimation

Adaptive beamformer is very sensitive to model mismatch, especially when the signal-of-interest is present in the training data. In this paper, we focus on the topic of robust adaptive beamforming (RAB) based on interference-plus-noise covariance matrix (INCM) reconstruction. First, we analyze the effectiveness of several INCM reconstruction schemes, and particularly analyze the impacts of interference power estimation on RAB. Second, according to the analysis results, we develop a simplified algorithm to estimate the interference powers, and a RAB algorithm based on INCM reconstruction is then presented. Compared with some existing methods, the proposed algorithm simplifies the interference power estimation of INCM reconstruction. Aligned with our analysis, simulation results demonstrate that the overestimation of interference powers hardly degrades the performance of adaptive beamforming, and our proposed algorithm achieves nearly optimal performance across a wide range of signal-to-noise ratios.

Multiple constrained minimum variance beamformer (MCMV) performance in connectivity analyses

Functional brain connectivity is increasingly being seen as critical for cognition, perception and motor control. Magnetoencephalography and electroencephalography are modalities that offer noninvasive mapping of electrophysiological interactions among brain regions, yet suffer from signal leakage and signal cancellation when estimating brain activity. This leads to biased connectivity values which complicate interpretation. In this study, we test the hypothesis that a Multiple Constrained Minimum Variance beamformer (MCMV) outperforms the more traditional Linearly Constrained Minimum Variance beamformer (LCMV) for estimation of electrophysiological connectivity. To this end, MCMV and LCMV performance is compared in task related analyses with both simulated data and human MEG recordings of visual steady state signals, and in resting state analyses with simulated data and human MEG data of 89 subjects. In task related scenarios connectivity was estimated using coherence and phase locking values, whereas envelope correlations were used for the resting state data. We also introduce a novel Augmented Pairwise MCMV (APW-MCMV) approach for signal leakage suppression in resting state analyses and assess its performance against LCMV and more conventional MCMV approaches. We demonstrate that with MCMV effects of signal mixing and coherent source cancellation are greatly reduced in both task related and resting state conditions, while in contrast to other approaches 0- and short time lag interactions are preserved. In addition, we demonstrate that in resting state analyses, APW-MCMV strongly reduces spurious connections while better controlling for false negatives compared to more conservative measures such as symmetrical orthogonalization.

Adaptive Beamforming Design for Millimeter-Wave Line-of-Sight MIMO Channel

In this letter, we propose dictionary learning (DL) algorithm to solve the hybrid beamforming of millimeter-wave (mmWave) line-of-sight (LoS) multiple-input multiple-output (MIMO), which is modeled by Ray-tracing principal. Additionally, the number of transmitted data streams is adaptively adjusted by the effective degree of freedom (EDoF). The numerical simulation shows that the performance of hybrid beamforming based on the proposed algorithm can approach the optimal performance of full digital beamforming. Moreover, the adaptive hybrid beamforming of mmWave LoS MIMO can achieve the maximum spectral efficiency regardless of any number of transmitted data streams.

A Novel 2-D $3\times3$ Nolen Matrix for 2-D Beamforming Applications

In this paper, a 2-D beamforming phased array using a novel 2-D Nolen matrix network is presented. The Nolen matrix is a novel antenna feeding network composed of only couplers with dedicated coupling ratios and phase shifters. It does not require crossover and load termination compared to other networks based on Butler and Blass matrix. To be specific, the closed-form equations are derived first for uniplanar single $3 \times 3$ Nolen matrix, which is composed of three couplers and three phase delay lines. Most importantly, it is found that the proposed Nolen matrix can employ couplers with arbitrary phase differences to achieve relatively flexible progressive phase delays across the radiating elements, presenting a high degree of freedom on circuit topology and beamforming performance. Then, a 2-D antenna feeding network is designed by stacking and cascading six $3 \times 3$ Nolen matrices, and a 2-D patch antenna array is integrated with the proposed feeding network to generate nine radiation beams with unique directions on azimuth and elevation planes, realizing the 2-D beamforming function. To verify the proposed design concept, a prototype of 2-D beamforming phased array operating at 5.8 GHz is designed, fabricated, and measured, and the experimental results agree well with simulation and theoretical analysis.

Channel equalisation method for wideband digital array radar

In the radar systems, such as frequency source, power amplifier, mixer, filter and A/D converter, ageing devices, temperature and environmental changes etc., it is inevitable to introduce wideband amplitude/phase error. These can cause seriously channel mismatch that will affect the performance of digital beam-forming, synthetic aperture radar image, space time adaptive processing (STAP), automatic target recognition (ATR), target detection, clutter/interference suppression, pulse compression results and cancellation ratio etc. So this study mainly discusses that the channel amplitude/phase inconsistency of wideband digital array radar affects the pulse compression, beam forming and so forth. It also researches and analyses channel equalisation method, and the simulation and experimental results based on the experimental data show that the method based on Fourier transform is effectively and convenient. The Fourier transform method is easier for hardware implementation that can be applied to practical engineering.

A Novel Constrained Waveform Designing for MIMO RADAR Using Optimization Algorithms

MIMO RADAR system is efficacious in forming the desired beampattern by using transmit waveform design methodology. In this work, a distinctive approach is carried out to design null-steered transmit beamforming through discrete polyphase-coded waveforms. These waveforms are optimized and analysed in space domain and also checked for orthogonality in time domain. The cost function is inducted in order to achieve radiation nulls in the direction of the jammer, other radars, undesired target, etc. Besides widely held optimization algorithms, a novel metaheuristic approach namely “Jaya” algorithm is dealt with, implemented and compared in the designing of traditional and polyphase waveforms. Unlike other population-based algorithms, the absence of algorithm-specific parameters makes it computationally effective. The proposed approach applied post optimization process satisfies the design constraint for creating discrete-valued phases. “Jaya” optimization with regard to the polyphase waveform design, in space domain endows the least radiation null notch of dB. The design time metric is also significantly minimized. Further, the effect of phase error on the designed beampatterns are analysed. The proposed method offers a reasonable trade-off between the number of design constraints and beamformer performance even in the erroneous environment. A higher value of M in M-phase-coded waveform guarantees robust beamforming specifically in multiple nulls scenarios. The approaches are validated with mathematical modelling and numerical simulations.

Hybrid Sparse Array Beamforming Design for General Rank Signal Models

The paper considers sparse array design for receive beamforming achieving maximum signal-to-interference plus noise ratio (MaxSINR) for both single point source and multiple point sources, operating in an interference active environment. Unlike existing sparse design methods which either deal with structured environment-independent or non-structured environment-dependent arrays, our method is a hybrid approach and seeks a full augumentable array that optimizes beamformer performance. This approach proves important for limited aperture that constrains the number of possible uniform grid points for sensor placements. The problem is formulated as quadratically constraint quadratic program (QCQP), with the cost function penalized with weighted l_1-norm squared of the beamformer weight vector. Simulation results are presented to show the effectiveness of the proposed algorithms for array configurability in the case of both single and general rank signal correlation matrices. Performance comparisons among the proposed sparse array, the commonly used uniform arrays, arrays obtained by other design methods, and arrays designed without the augmentability constraint are provided.

Experimental study on source direction finding using a cylindrical array considering scattered sound fields

A circular array is widely used for source direction finding due to its more compact configuration and smaller angular dependency compared to a linear array. In underwater environments, however, high drag forces make it difficult to utilize the circular array especially for the case where there is high-speed ocean current or the platform with the array is moving. To overcome this operational difficulty an array of hydrophones flush mounted on a cylindrical structure may be applied. A recent numerical study shows that the beamforming performance is improved by considering the scattered sound field by a cylinder. Recently, a tank experiment using an array of eight receiver element on a cylindrical structure has been done for underwater source direction finding. In the experiment narrowband and wideband signals are used for the sound transmitter. The experimental results also show that the lower side-lobes are obtained when the scattering effect is considered during beamforming analysis. [This work is financially supported by the research project PES3180 funded by KRISO.]

Modified Eigenspace Based Iterative Robust Capon Beamformer

To improve the performance of adaptive beamformer with large steering vector mismatch, a modified eigenspace based iterative robust capon beamformer (ME-IRCB) is proposed. The approach iteratively implements the robust Capon beamformer (RCB) with an adaptively adjusted uncertainty set. Based on the modified eigenspace method, the desired signal subspace is given, whereafter the size of the uncertainty set is adaptively adjusted according to the mismatch between the estimated and presumed steering vector of the desired signal at each iteration. The proposed approach gives two estimation methods about the uncertainty size, and both of them contribute to the robustness improving of the beamformer. Moreover, unlike other robust beamformers, the proposed approach does not take the integration of the steering vector’s outer product over the adjacent direction of the desired signal, and it works well with the adjacent directions of the desired signal and interference. This merit is due to that, the proposed approach only uses the fundamental sample covariance matrix during the subspace construction, therefore the influence of imprecise steering vector on the subspace is overcame. Simulation results show that the proposed approach performs better than the existing robust beamformers under different evaluation criteria.

An improved algorithm for radar adaptive beamforming based on machine learning

In the field of radar digital signal processing, adaptive beamforming is a widely used technique for suppressing interference and noise. The Least Mean Square Algorithm (LMS) is a simple and easy algorithm for adaptive digital beamforming. However, it has the disadvantage of not achieving a balance between convergence speed and stability. In order to improve the performance of adaptive beamforming, this paper firstly reviews the classical LMS algorithm and then the machine learning optimization algorithm. Improvement effects of the three machine learning methods on the LMS algorithm are analyzed. The results show that the improved LMS algorithm based on AdaGrad exhibits the best performance. The algorithm can independently adjust the adaptive learning rate of different parameter components, making the iterative process of the adaptive beamforming more stable, efficient, and suitable for both theoretical research and engineering practice.

Low-Sidelobe Range-Angle Beamforming With FDA Using Multiple Parameter Optimization

In this paper, we propose an equivalent transmit beamforming method in joint range and angle domains at the receiver of the colocated transmit-receive system where frequency diverse array (FDA) acts as transmit antenna. FDA employs a small frequency offset across the array elements and introduces additional degrees-of-freedom in range domain, which can significantly enhance the beamforming flexibility. However, the transmit beampattern of conventional FDA is range-angle-time dependent. In this work, the time-varying problem is first solved by using a series of filters and mixers at the receiver. In the sequel, a subarray-based FDA framework, termed as multisub-FDA, is established and then a range-angle-decoupled equivalent transmit beamforming method is devised based on particle swarm optimization, which incorporates the frequency offset of each subarray and the corresponding weight vector into the optimization problem. With the proposed approach, the array is capable of generating focused beampattern with low sidelobe in both range and angle domains. Numerical results show that the proposed algorithm improves the beamforming performance, range resolution, and sidelobe suppression.

Robust adaptive beamforming method based on desired signal steering vector estimation and interference‐Plus‐noise covariance matrix reconstruction

Here, the authors propose a robust adaptive beamforming method based on desired signal steering vector estimation and interference-plus-noise covariance matrix reconstruction, so as to attenuate the influences of the desired signal steering vector mismatch and the limited training snapshots on the performance of adaptive beamformer. More precisely, the desired signal steering vector is estimated by minimising the sine value of the angle between the presumed desired signal steering vector and the eigenvectors of sample covariance matrix. Besides, the sample covariance matrix is reconstructed by reducing the dispersion extent of the noise eigenvalues and eliminating the desired signal component from the sample covariance matrix. The proposed method can not only accelerate the convergence speed of adaptive beamforming algorithm, but also avoid the desired signal cancellation phenomenon when the desired signal is present in the training snapshots. Simulation results demonstrate the superiority of the proposed method.

Robust adaptive beamforming with low sensitivity for mutual coupling based on auxiliary elements

The performance of the conventional adaptive beamformer undergoes degradation in the presence of the mutual coupling between the neighbouring elements. To eliminate the sensitivity for the MC, the dummy elements are fixed around the array. Here, the authors demonstrate the optimal layers of auxiliary elements for uniform rectangular array (URA) in the case of the specific MC model and give the concrete theoretical proof. The corresponding derivation proves that only one layer of auxiliary elements is needed to tackle with the MC effect, and the output SINR and beampattern are improved by means of the proposed method for URA. Finally, the simulation results have shown the effectiveness of authors’ method.

CABE: A Cloud-Based Acoustic Beamforming Emulator for FPGA-Based Sound Source Localization.

Microphone arrays are gaining in popularity thanks to the availability of low-cost microphones. Applications including sonar, binaural hearing aid devices, acoustic indoor localization techniques and speech recognition are proposed by several research groups and companies. In most of the available implementations, the microphones utilized are assumed to offer an ideal response in a given frequency domain. Several toolboxes and software can be used to obtain a theoretical response of a microphone array with a given beamforming algorithm. However, a tool facilitating the design of a microphone array taking into account the non-ideal characteristics could not be found. Moreover, generating packages facilitating the implementation on Field Programmable Gate Arrays has, to our knowledge, not been carried out yet. Visualizing the responses in 2D and 3D also poses an engineering challenge. To alleviate these shortcomings, a scalable Cloud-based Acoustic Beamforming Emulator (CABE) is proposed. The non-ideal characteristics of microphones are considered during the computations and results are validated with acoustic data captured from microphones. It is also possible to generate hardware description language packages containing delay tables facilitating the implementation of Delay-and-Sum beamformers in embedded hardware. Truncation error analysis can also be carried out for fixed-point signal processing. The effects of disabling a given group of microphones within the microphone array can also be calculated. Results and packages can be visualized with a dedicated client application. Users can create and configure several parameters of an emulation, including sound source placement, the shape of the microphone array and the required signal processing flow. Depending on the user configuration, 2D and 3D graphs showing the beamforming results, waterfall diagrams and performance metrics can be generated by the client application. The emulations are also validated with captured data from existing microphone arrays.

Analytical Framework for Full-Dimensional Massive MIMO With Ray-Based Channels

The performance of baseband beamforming in multi-user multiple-input multiple-output (MU-MIMO) systems has been extensively studied for simplified statistical channel models where no angular parameters are taken into account. In contrast, there is little performance analysis with ray-based models, which are more physically motivated, feature prominently in standardization and have been experimentally validated. Thus, unlike previous studies, we present a mathematical framework to analyze the performance of zero forcing (ZF) and minimum mean-squared error (MMSE) combining. Using a central result for averaging in the angular domain, we derive tight approximations for the uplink signal-to-noise ratio and signal-to-interference-and-noise ratio (SINR) for ZF and MMSE processing, respectively, and the resulting spectral efficiencies. The remarkably simple expressions offer the following insights into the effects of the propagation environment. We demonstrate an improvement in performance when moving from vertical uniform rectangular array (URA) to horizontal URA to uniform linear array (ULA) antenna configurations. There is also a corresponding increase in the robustness of the performance to propagation scenarios. We demonstrate that under specific conditions increasing the angular spread can decrease the SINR for a ULA - an unexpected behavior which we link to the effects of end-fire radiation. Furthermore, our results allow us to investigate the impact of different array configurations and system parameters on the rate of convergence to favorable propagation conditions. Finally, we evaluate the spatial correlation properties intrinsically present in ray-based models, and compare them to the commonly used simple exponential model which yields equal, fixed correlation characteristics for each user.

Terahertz-Band Ultra-Massive Spatial Modulation MIMO

The prospect of ultra-massive multiple-input multiple-output (UM-MIMO) technology to combat the distance problem at the Terahertz (THz) band is considered. It is well-known that the very large available bandwidths at THz frequencies come at the cost of severe propagation losses and power limitations, which result in very short communication distances. Recently, graphene-based plasmonic nano-antenna arrays that can accommodate hundreds of antenna elements in a few millimeters have been proposed. While such arrays enable efficient beamforming that can increase the communication range, they fail to provide sufficient spatial degrees of freedom for spatial multiplexing. In this paper, we examine spatial modulation (SM) techniques that can leverage the properties of densely packed configurable arrays of subarrays of nano-antennas, to increase capacity and spectral efficiency, while maintaining acceptable beamforming performance. Depending on the communication distance and the frequency of operation, a specific SM configuration that ensures good channel conditions is recommended. We analyze the performance of the proposed schemes theoretically and numerically in terms of symbol and bit error rates, where significant gains are observed compared to conventional SM. We demonstrate that SM at very high frequencies is a feasible paradigm, and we motivate several extensions that can make THz-band SM a future research trend.

Low-Complexity Failed Element Diagnosis for Radar-Communication mmWave Antenna Array with Low SNR

The millimeter-wave (mmWave) antenna array plays an important role in the excellent performance of wireless sensors networks (WSN) or unmanned aerial vehicle (UAV) clusters. However, the array elements are easily damaged in its harsh working environment but hard to be repaired or exchanged timely, resulting in a serious decline in the beamforming performance. Thus, accurate self-diagnosis of the failed elements is of great importance. In previous studies, there are still significant difficulties for large-scale arrays under extremely low SNR. In this paper, a diagnosis algorithm with low complexity and high reliability for the failed elements is proposed, which is based on a joint decision of communication signal and sensing echoes. Compared with the previous studies, the complexity of the algorithm is reduced by the construction of low-dimensional feature vectors for classification, the decoupling of the degree of arrival (DOA) estimation and the failed pattern diagnosis, with the help of the sub-array division. Simulation results show that, under an ultra-low SNR of −12.5 dB for communication signals and −16 dB for sensing echoes, an accurate self-diagnosis with a block error rate lower than 8% can be realized. The study in this paper will effectively promote the long-term and reliable operation of the mmWave antenna array in WSN, UAV clusters and other similar fields.

Hybrid and full-digital beamforming in mmWave Massive MIMO systems: A comparison considering low-resolution ADCs

In a millimeter-wave (mmWave) Massive multiple-input multiple-output (MIMO) systems, full-digital beamforming (i.e., connecting each antenna with a specific radio-frequency (RF) chain) becomes inefficient due to the hardware cost and power consumption. Therefore, hybrid analog and digital transceiver where the number of RF chains are much smaller than that of the antennas has drawn great research interest. In this work, we investigate the use of low-resolution analog-to-digital converters (ADCs) in the uplink of multi-user hybrid and full-digital mmWave Massive MIMO systems. To be specific, we compare the performance of full-digital minimum mean square error (MMSE) and hybrid MMSE beamforming in both sum rates and energy efficiency. Accurate approximations of sum rates and energy efficiency are provided for both schemes, which captures the dominant factors. The analytical results show that full-digital beamforming outperforms hybrid beamforming in terms of sum rates and requires only a small portion (γ) of antennas used by hybrid beamforming to achieve the same sum rates. We given sufficient condition for full-digital beamforming to outperform hybrid beamforming in terms of energy efficiency. Moreover, an algorithm is proposed to search for the optimal ADC resolution bits. Numerical results demonstrate the correctness of the analysis.

Experimental Demonstration of mm-Wave 5G NR Photonic Beamforming Based on ORRs and Multicore Fiber

A photonic beamformer system designed for next-generation 5G new radio (5G NR) operating in the millimeter waveband is proposed and demonstrated experimentally, including its performance characterization. The photonic beamforming device is based on optical ring resonators (ORRs) implemented on Si3N4 and assisted with multicore fiber (MCF) to feed different antenna elements (AEs). Fast-switching configuration of the ORRs is performed changing the operating wavelength, as tuning the wavelength modifies the coupling coefficient of the rings and, consequently, the induced time delay. Multibeam operation is evaluated at 17.6- and 26-GHz radio keeping the ORRs’ configuration. The beamforming performance is evaluated using single-carrier signals with up to 128 quadrature amplitude modulation over up to 4.2-GHz electrical bandwidth. The experimental beamforming system with two AEs provides up to 21 Gb/s per user, while the beamforming system with four AEs provides up to 16.8 Gb/s per user. Wireless transmission confirms that changing the wavelength from 1545.200 to 1545.195 nm modifies the beam steering from 11.3° to 23° with 26-GHz signals (5G NR pioneer band in Europe).