Array Size Increases Research Articles

A novel read circuit for RRAM based on RC delay effect

AbstractIn this paper, a novel Resistive Random‐Access Memory (RRAM) read circuit has been designed and verified by simulation based on the RRAM model and parasitic capacitance of the circuit. Simulation results demonstrate the feasibility and effectiveness of the proposed circuit, with accurate reading of RRAM states and fast reading speed in the nanosecond range. The sense margin of the proposed circuit has improved as the array size increases, enhancing its application for advanced node RRAM array manufacture. Compared with conventional circuits, the proposed circuit achieved power consumption reduction of 6% and area reduction of 46.9 um2, resulting in a 97.5% reduction in area, providing an effective solution to address the cost and chip size challenges associated with RRAM industrialization.

Measurement-Based 3-D Channel Modeling With Cluster-of-Scatterers Estimated Under Spherical-Wave Assumption

With the rapid development of the sixth generation (6G) communication systems, the extremely large antenna arrays (ELAAs) have attracted substantial attention in both academia and industry. As the array size increases, the so-called “near-field” effect, i.e. channel parameters varying with respect to the antenna’s position becomes evident. Conventional channel models fail to describe such effects as the parameters of multipath components (MPCs) specified in these models are fixed regardless of array configuration. Due to the mismatch between the constant MPC assumption and the actual variant behavior observed, the parameterization of the models aiming to describe the spatial non-stationary channels cannot be conducted effectively. In order to mitigate the model mismatch and reproduce the channels with spatial non-stationarity specifically for ELAA applications, in this work, a novel measurement-based stochastic channel modeling method is proposed and applied to establishing Scatterer-based Spatial Channel Model (SSCM) that can be used to unify the far- and near-field models using spherical wave and generate the spatial non-stationary channels for ELAAs by integrating the traditional spatial channel model (SCM) with “clusters-of-scatterers (CoS)”. To establish the models based on measurements, the locations of first- and last-hop scatterers existing along propagation paths in a channel are estimated based on the spherical-wave assumption. A novel clustering algorithm is used to group the MPCs taking into account those scatterers’ locations. With a channel measurement campaign conducted using a 32×32 Rx planar antenna array at carrier frequency of 10 GHz, exemplary SSCMs are established. The SSCM is capable of reproducing the parts of the environment influencing wave propagation, and therefore can be used for the research of integrated sensing and communication (ISAC) applications.

Wideband Inter-Beam Interference Cancellation for mmW/Sub-THz Phased Arrays With Squint

As relative bandwidth increases, beam squint, i.e., frequency dependent directivity, limits the wideband performance of phase-shifter steered arrays. This effect is already notable in 5G systems operating at 28 GHz and above with 400/800 MHz bandwidths, especially if broadband cancellation is needed between multiple beams. The wideband squinting effect reduces the signal-to-interference-plus-noise-ratio of a multibeam system by changing the level and direction of the spatial null towards the interferer. This paper examines the effectiveness of the inter-beam interference (IBI) cancellation using crosscoupled signals for wideband arrays with visible squint effect. For a large relative bandwidth of the array, this paper presents a component carrier-based approach for interference cancellation between the beams of different users or data streams. Furthermore, as bandwidth and array size increase, the impact of squint increases, which is also examined for the cancellation of the IBI. Furthermore, an example scenario is simulated using standard 5GNR modulated waveforms.

On the effect of array size on the radar cross section reduction bandwidth of checkerboard metasurfaces

Abstract This paper reports investigations on the effect of array size on the RCS reduction bandwidth of checkerboard metasurfaces (CMS). Three CMSs, one on a Rogers substrate and the remaining on FR4, are considered. While the usual phase deviation criteria are used for the designs on both the substrates, additionally a set of modified criteria recently proposed are used for the FR4 substrate-based designs. While three different sizes – 120 mm2, 240 mm2, and 480 mm2 – are considered for the simulation-based investigations for all the structures, an additional size of 600 mm2 is also considered for one of them. The 8 and 10 dB RCS reduction bandwidths drop as array size increases. The bandwidth reduction is attributable to mutual coupling, as has been reported in an earlier study. As therefore expected, all of the three structures, for all sizes, present the same RCS reduction bandwidth when a mutual coupling mitigation technique is incorporated. For 10 dB RCS reduction bandwidth, this value approaches that estimated by using a mutual coupling independent semi-empirical equation that holds for infinite arrays.

Modeling and Compensation of IR Drop in Crosspoint Accelerators of Neural Networks

In-memory computing (IMC) has the potential of accelerating data-intensive computing tasks, such as inference and training of neural networks, by the matrix vector multiplication (MVM) in the crosspoint array. As the array size increases, however, a significant problem arises due to the parasitic IR drop at row and column lines. Understanding and compensating IR drop is essential to enable high-density accelerators of MVM. This work presents an analytical model for the IR drop and a numerical algorithm capable of accelerating the nodal analysis of crosspoint arrays up to five orders of magnitude with respect to SPICE analysis. The numerical algorithm is used to study the impact of array size, data density, device/wire resistance, and nonlinearity on the IR drop and the related loss of accuracy in IMC. We also derive two simple compensation schemes and an architectural solution for the mitigation of IR drop that are able to increase the accuracy of neural networks from 59% up to 96.6%, compared to an ideal accuracy of 97%.

Dual-Polarized FDD Massive MIMO: A Comprehensive Framework

We propose a comprehensive scheme for realizing a massive multiple-input multiple-output (MIMO) system with dual-polarized antennas in frequency division duplexing (FDD) mode. Dual-polarized arrays are commonly employed due to the favorable property that, in principle, they can double the number of channel spatial degrees of freedom with a less-than-proportional increase in array size. However, processing a dual-polarized massive MIMO channel is demanding due to the high channel dimension and the lack of Uplink-Downlink (UL-DL) channel reciprocity in FDD mode. In particular, the difficulty arises in common channel training and DL precoding in a multi-user setup. To address this, we develop a unified framework consisting of three steps: (1) covariance estimation to efficiently estimate the UL covariance from noisy UL pilots; (2) a UL-DL covariance transformation method that obtains the DL covariance from the estimated UL covariance, eliminating the need for DL channel covariance training via pilot transmission; <xref ref-type="disp-formula" rid="deqn3a-deqn3b" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(3)</xref> a joint multi-user DL channel training method, which enables the BS to estimate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">effective DL channels</i> given any protocol-specific pilot dimension and to use them for interference-free DL beamforming and data transmission. Through extensive simulations, we show that our scheme is applicable to a variety of communication scenarios in terms of the number of antennas, UL and DL pilot dimensions, and angular scattering properties. Unlike the common trend in the literature, we do <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">not</i> make strong structural assumptions about the wireless channel (such as angular sparsity), ensuring a general treatment of the problem.

Improved Hopfield Network Optimization Using Manufacturable Three-Terminal Electronic Synapses

We illustrate novel optimization techniques via simulations for Hopfield networks constructed from manufacturable three-terminal Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) synaptic circuit elements. We first present a computationally-light, memristor-based, highly accurate static compact model for the SONOS synapses used in our simulations. We then show how to exploit analog errors in programming resistances and current leakage, and the continuous tunability of the SONOS synapses to enable transient chaotic group dynamics, to accelerate the convergence of a Hopfield network. We project improvements in energy consumption and time to solution relative to existing CPUs and GPUs by at least 4 orders of magnitude, and also exceed the projected performance of two-terminal memristor-based crossbars in addition to a 100-fold increase in error-resilient array size (i.e. problem size).

Protein-Protein Interactions Induce pH-Dependent and Zeaxanthin-Independent Photoprotection in the Plant Light-Harvesting Complex, LHCII.

Plants use energy from the sun yet also require protection against the generation of deleterious photoproducts from excess energy. Photoprotection in green plants, known as nonphotochemical quenching (NPQ), involves thermal dissipation of energy and is activated by a series of interrelated factors: a pH drop in the lumen, accumulation of the carotenoid zeaxanthin (Zea), and formation of arrays of pigment-containing antenna complexes. However, understanding their individual contributions and their interactions has been challenging, particularly for the antenna arrays, which are difficult to manipulate in vitro. Here, we achieved systematic and discrete control over the array size for the principal antenna complex, light-harvesting complex II, using near-native in vitro membranes called nanodiscs. Each of the factors had a distinct influence on the level of dissipation, which was characterized by measurements of fluorescence quenching and ultrafast chlorophyll-to-carotenoid energy transfer. First, an increase in array size led to a corresponding increase in dissipation; the dramatic changes in the chlorophyll dynamics suggested that this is due to an allosteric conformational change of the protein. Second, a pH drop increased dissipation but exclusively in the presence of protein-protein interactions. Third, no Zea dependence was identified which suggested that Zea regulates a distinct aspect of NPQ. Collectively, these results indicate that each factor provides a separate type of control knob for photoprotection, which likely enables a flexible and tunable response to solar fluctuations.

Retention enhancement through capacitance-dependent voltage division analysis in 3D stackable TaOx/HfO2-based selectorless memristor

Sneak path current generated by adjacent cells in three-dimensional (3D) memristor arrays must be curbed while securing the multi-bit storage capability of each cell to aid in the cost-effective increase in array size. For this purpose, a 3D stackable TaOx/HfO2-based selectorless memristor has been proposed and optimized via capacitance-dependent voltage division analysis. The proposed device utilizes the formation or rupture of conductive filaments for self-rectifying resistive switching operation, in contrast to nonfilamentary devices that often exploit the change in the charge state of the electron trap. This approach enables the reduction of the trapped charge leakage through the interface between the resistive switching and metal layers effectively, giving rise to excellent retention properties (>5 × 105 s). Furthermore, the proposed device exhibits a sufficiently high on/off ratio (~1.35 × 103), rectification ratio (~2.3 × 103), endurance (1.5 × 102 cycles), and low resistance variation (standard deviation <0.022). Moreover, multilevel operations are facilitated, making the proposed device suitable for high-density, nonvolatile memory applications.

Steering Vector Transformation Technique for the Design of Point Sources Wideband Beamforḿer.(Dept.E)

Steering vector transformation technique for wideband antenna array of point sources is presented. Wideband direction of arrival (DoA) estimation using this technique is illustrated. In the present work, steering vector transformation is applied to the conventional frequency domain beamformer to enhance the frequency invariance of the mainlobe pattern. Several simulation examples are presented to illustrate the advantage of the proposed frequency domain beamformer over the conventional one. As the array size increases or the interelement spacing decreases, the proposed beamformer still has a better frequency invariant property of the mainlobe pattern than the conventional beamformer. Finally, using windows, a better frequency invariant property of the mainlobe patter is obtained by the proposed beamformer than the conventional one.

Cluster formation and non-metal-to-metal transition in a diamond-shaped graphene-like lattice

This work is a numerical simulation of the bond percolation in an array of junctions and bifurcations mimicking a section of a graphene slab. We calculate the size distribution of graphene clusters as a filler of a polymer aiming to obtain the percolation threshold. We obtained the sigmoidal distribution of graphene clusters as a function of concentration of persistent conducting bonds creating these clusters. The probability density of this distribution shows a universal complementary Fermi–Dirac behavior as a signature of a topological response. Using a tight-binding model for the transmission from the source to the drain, we obtain a smooth transition from an insulator to a conductor through a dirty metal as the concentration of conductive bonds increases for small arrays. As the array size increases, the simulation shows a sharp non-metal-to-metal transition from a pure polymer into a pristine suspended graphene layer.

Full-Duplex mmWave Massive MIMO Systems: A Joint Hybrid Precoding/Combining and Self-Interference Cancellation Design

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems have been considered as one of the primary candidates for the fifth generation (5G) and beyond 5G wireless communication networks to satisfy the ever-increasing capacity demands. Full-duplex technology can further enhance the advantages of mmWave massive MIMO systems. However, strong self-interference (SI) is the major limiting factor in full-duplex technology. Hence, this paper proposes a novel angular-based joint hybrid precoding/combining (AB-JHPC) technique for the full-duplex mmWave massive-MIMO systems. Our primary goals are listed as: (i) improving the self-interference cancellation (SIC), (ii) increasing the intended signal power, (iii) decreasing the channel estimation overhead, (iv) designing the massive MIMO systems with a low number of RF chains. First, the RF-stage of AB-JHPC is developed via slow time-varying angle-of-departure (AoD) and angle-of-arrival (AoA) information. A joint transmit/receive RF beamformer design is proposed for covering (excluding) the AoD/AoA support of intended (SI) channel. Second, the BB-stage of AB-JHPC is constructed via the reduced-size effective intended channel. After using the well-known singular value decomposition(SVD) approach at the BB-stage, we also propose a new semi-blind minimum mean square error (S-MMSE) technique to further suppress the residual SI power by using AoD/AoA parameters. The numerical results demonstrate that the SI signal is remarkably canceled via the proposed AB-JHPC technique. It is shown that AB-JHPC achieves 85.7 dB SIC and the total amount of SIC almost linearly increases via antenna isolation techniques. We observe that the proposed full-duplex mmWave massive MIMO systems double the achievable rate capacity compared to its half-duplex counterpart as the antenna array size increases and the transmit/receive antenna isolation improves.

Modeling energy exchange and heating within nanorod arrays due to near-field radiative coupling

We present a heat transfer model to obtain the temperature distribution within aligned nanorod arrays. The model includes thermal conduction along each nanorod in addition to a phenomenological treatment of near-field radiative energy exchange among the nanorods and allows us to investigate the interplay between these effects. The contribution of the near-field radiative energy exchange to overall heating is found to increase significantly with a decrease in inter-nanorod spacing and an increase in array size; the effect is also more prominent for nanorods with lower thermal conductivity and higher emissivity.

Synthesis of Large Unequally Spaced Planar Arrays Utilizing Differential Evolution With New Encoding Mechanism and Cauchy Mutation

This article presents a differential evolution algorithm with a new encoding mechanism and Cauchy mutation (DE-NEM-CM) for optimizing large unequally spaced planar array layouts with the minimum element spacing constraint. In the new encoding mechanism, each individual represents a certain element position rather than an entire array layout used in traditional stochastic optimization algorithms. Such an encoding mechanism has the following advantages: 1) in each individual updating, the array pattern can be efficiently evaluated by only considering the radiation contribution variation from one element movement, which can greatly reduce the computational time; 2) it naturally facilitates the generated new array layout in population updating to meet the minimum element spacing constraint, and 3) each individual is searched always in 2-D space as the array size increases. These advantages enable it to be very suitable for synthesizing large arrays. Besides, DE serves as a search engine, and Cauchy mutation with chaotic mapping is proposed to enhance the local search while preserving the diversity of the population. A set of experiments for synthesizing different types of unequally spaced planar arrays in both narrow-and broadband applications are conducted. Synthesis results show that the proposed method achieves much lower sidelobe level than some state-of-the-art stochastic optimization methods for all the test cases. Importantly, the proposed method is much more efficient than conventional stochastic optimization algorithm especially for the case of synthesizing large unequally spaced planar array layouts. A array layout optimization with more than 1000 elements can be achieved within acceptable CPU time cost, which has not yet been reported for the existing stochastic optimization methods without resorting to supercomputing facilities.

ADMM-based transmit beampattern synthesis for antenna arrays under a constant modulus constraint

Transmit beampattern synthesis for antenna arrays is addressed in this paper. In pursuit of high radiation efficiency, most phased array radar systems utilize nonlinear power amplifiers, which leads to a constant modulus constraint for transmit weight vector optimization. Existing methods to solve this hard nonconvex problem (unit-modulus quadratic program) generally have high computational cost and large memory burden, which may increase dramatically as the array size increases. To that end, we propose a low-complexity algorithm based on the alternating direction method of multipliers (ADMM) framework. By introducing auxiliary variables, the original problem is decomposed into several subproblems with closed-form solutions. The transmit weight vector and the phase response of the desired beampattern is updated alternately so that the cost function value can be monotonically reduced. With bounded penalty parameters, the proposed ADMM-based algorithm can guarantee to converge. We further prove that the converged solution satisfies the Karush-Kuhn-Tucker conditions of the nonconvex optimization problem. Numerical simulation results confirm the effectiveness of the proposed method.

Improved Over-the-Air Phased Array Calibration Based on Measured Complex Array Signals

This letter presents an improved phased array calibration method based on measured complex array signals with one single probe. All the phased array elements are excited simultaneously in the measurement, and only phase reverse of each element is required. The error on the first antenna element of the reference method is analyzed, which shows it is accumulated as the array size increases. One more measurement with designed element phase settings is introduced to overcome the deficiency. The improved method shows that only $N+1$ measurements are required to calibrate $N$ antenna elements accurately. Finally, a $4\times 8$ antenna array composed of 4-ridged horn antennas operating at 3.5 GHz was measured to validate the effectiveness of the improved algorithm.

Performance analysis of a parameter‐tuned bistable parallel array system for binary pulse amplitude modulation signal processing

In order to improve the signal-to-noise ratio (SNR) gain and lower the bit error rate (BER) when a weak signal is buried in the noise, the parameter-tuned stochastic resonator (PSR) is studied in more detail. In this study, the authors explore the impact of the number of branches on performance. Hence, they build the parameter-tuned bistable parallel array system, which consists of a group of PSRs and propose a novel method to derive the probability density function (PDF) of the output signal, which combines the conventional PDF based on the approximation theory with Gaussian distribution. Based on this method, an analytical expression for BER of the system is derived. It is of interest to note that for an input binary pulse amplitude modulation signal buried in noise, the weak signal can be detected by using the parameter-tuned bistable parallel array system. It is found that via the array PSR effect, the system output SNR gain can be improved. Moreover, the BER can also be reduced with the increase of the array size as the array size increases.

Filter Bank Multicarrier in Massive MIMO: Analysis and Channel Equalization

We perform an asymptotic study of the performance of filter bank multicarrier (FBMC) in the context of massive multi-input multi-output (MIMO). We show that the effects of channel distortions, i.e., intersymbol interference and intercarrier interference, do not vanish as the base station (BS) array size increases. As a result, the signal-to-interference-plus-noise ratio (SINR) cannot grow unboundedly by increasing the number of BS antennas, and is upper bounded by a certain deterministic value. We show that this phenomenon is a result of the correlation between the multi-antenna combining tap values and the channel impulse responses between the mobile terminals and the BS antennas. To resolve this problem, we introduce an efficient equalization method that removes this correlation, enabling us to achieve arbitrarily large SINR values by increasing the number of BS antennas. We perform a thorough analysis of the proposed system and find analytical expressions for both equalizer coefficients and the respective SINR.

Simulation of large photovoltaic arrays

Large photovoltaic arrays are becoming common as the world moves to replace fossil-fuelled electricity generators. As the array size and project cost increase, it becomes increasingly important to know accurately what the array’s performance will be before it is built. Large arrays inevitably contain modules with a spread of performance characteristics such as short-circuit current and open-circuit voltage, and suffer from temperature differences between modules. In this first study of these problems, a model has been developed that accurately predicts the behaviour of a photovoltaic array subject to variability between modules and inhomogeneity of cell temperature across the array. The model was applied to a real rooftop array consisting of 912 modules (298 kW nominal peak power). Based on measured string currents, the predicted average string temperature was compared the temperature measured by a radiometric survey using a drone-mounted IR camera and matched very well.The five-parameter model of cell I-V characteristics was fitted to manufacturer’s data, with highest weighting given to the region around the maximum-power point (MPP) where a real array should operate via active MPP tracking. The model was used to explore separately the effects of a spread in module characteristics arising in the manufacturing process and of temperature inhomogeneity across the array. The current in each module of a string was constrained to be the same, and the voltage of every parallel-connected string was also constrained to be the same. These constraints lead to greater power loss than is predicted based on an average module at an average temperature. Compared to a hypothetical array assembled from identical average modules at the same average temperature, variability caused a loss of power of about 2%, depending on the detailed form of the distribution function chosen to represent the spread of characteristics in the manufacturer’s tolerance band. As a rule of thumb, de-rating the maximum power to the lower end of the manufacturer’s tolerance band is recommended to account for module variability during the design phase. The effect of temperature inhomogeneity is more serious, because temperature affects Voc strongly, causing parallel-connected strings to be pulled away from their ideal operating points to obey the constraint of equal voltage. A modest 10 °C temperature gradient across the studied array was predicted to cause about a 4% loss of power at the MPP. Much higher real temperature differences could be expected in summer and were observed. The study confirmed that temperature inhomogeneity poses a serious design problem for large arrays, requiring careful thermal design to achieve not only acceptably low average array temperature, but also the least possible temperature spread.

Device and Circuit Interaction Analysis of Stochastic Behaviors in Cross-Point RRAM Arrays

Stochastic behaviors of resistive random access memory (RRAM) play an important role in the design of cross-point memory arrays. A Monte Carlo (MC) compact model of oxide RRAM is developed and calibrated with experiments on various device stack configurations. With MC SPICE simulations, we show that an increase in array size and interconnect wire resistance will statistically deteriorate write functionality. Write failure probability (WFP) has an exponential dependence on device uniformity and supply voltage (V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DD</sub> ), and the array bias scheme is a key knob. Lowering array V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DD</sub> leads to higher effective energy consumption (EEC) due to the increase in WFP when the variation statistics are included in the analysis. Random access simulations indicate that data sparsity statistically benefit write functionality and energy consumption. Finally, we show that a pseudo-subarray topology with uniformly distributed preforming cells in the pristine high-resistance state is able to reduce both WFP and EEC, enabling higher net capacity for memory circuits due to improved variation tolerance.