Multiple-input Single-output Research Articles

On the performance of STBC-NOMA assisted overlay cognitive system under CEEs and imperfect SIC

In future wireless networks, the synergy of non-orthogonal multiple access (NOMA) and cognitive radio (CR) can provide higher spectral efficiency and increased data rate. In this context, this article studies the performance of a space-time block code-aided overlay cognitive NOMA system based on Alamouti's (2 x 1, multiple-input single-output) code under the practical consideration of channel estimation errors (CEEs) and imperfect implementation of successive interference cancellation (SIC) at the receiver. We evaluate the closed-form expressions, after approximation, for the system throughput (ST) and outage probability (OP) over Rayleigh fading channels for both the secondary and primary networks. Asymptotic expressions of the OP and ST at high signal-to-noise ratio region are also evaluated to obtain further insights into the proposed scheme. Further, the article investigates the impact of various parameters on the OP and ST of the proposed scheme. Moreover, the OP of STBC orthogonal multiple access (OMA) based overlay cognitive network is also determined and compared with the presented network. Finally, simulations are used to validate the performance analysis of the proposed network and the accuracy of the derived analytical results. The simulation result shows that the presented system achieves significant gain in terms of the OP and ST compared to the STBC-OMA based overlay cognitive system and a recently proposed scheme under imperfect SIC and CEE conditions.

Identification of Continuous-Time Systems with Multiple Unknown Time Delays from Sampled Data

The purpose of this work is to identify a multiple-input single-output (MISO) continuous time (CT) system with various unknown time delays using sampled data. A novel technique for simultaneously estimating system parameters and various time delays may be developed using a gradient algorithm. Indeed, we propose a new formulation of the identification problem which permits defining the generalized vector containing the time delays and the dynamic parameters. The gradient optimization algorithm with exact derivatives of the objective function with respect to the adjustable parameters has been suggested as an alternative for solving this optimization problem. The identification method can be easily implemented by a filtering procedure to generate the input/output time derivatives. In this sense, the proposed method, which is based on a state variable filter, intrinsically allows data filtering and thus simplifies the use of the method in a practical case. An analysis is then presented which proves the convergence of the algorithm, and robustness issues are discussed as well. Finally, the suggested technique is evaluated on simulated instances to ensure its validity and performance.

Physical layer security for indoor GSM VLC

We consider the physical layer security (PLS) of the generalized spatial modulation (GSM) enabled indoor multiple-input single-output (MISO) visible light communication (VLC) downlink, wherein an optical artificial noise (OAN)-assisted scheme is proposed to enhance the secrecy of the considered system. Due to the transmitter (Alice) sending confidential messages and OAN with the power and amplitude constraints, a truncated Gaussian distribution is exploited. With a finite discrete distribution of the input signals, the secrecy performance is analyzed in the OAN-assisted GSM VLC system. Specifically, the average mutual information (AMI) is first proposed, then the lower bound and approximation of AMI, and the achievable secrecy rate (ASR) are evaluated as well. In addition, considering the proposed power allocation problem of the considered OAN-assisted GSM VLC system, the particle swarm optimization (PSO) algorithm is explored to attain the global optimal power allocation coefficient, which is capable of maximizing the ASR. The numerical and simulation results validate our theoretical results of the OAN-assisted secrecy performance of the considered indoor GSM VLC system.

Metamutator based universal, single input multi output current mode filter

AbstractThe introduction of Add ‐ Differentiate IC, AD‐IC, a new integrated circuit, into schemes for realizing single input multiple output current mode filters is the motivation behind this paper. In the circuit structure of this filter with only one active device with a minimal number of transistors and five passive components are being used. Non ideal effects of the design are investigated and simulation results of the application, using TSMC 0.25 μm process parameters with ±1.25 V power supply voltage and the bias as 0.8 V resulting in 0.99 mW power dissipation for the entire filter, are also presented to confirm the theoretical analysis. With this new design technique, the tunabilities of the angular frequency ( ) and quality factor ( ) can be performed independently.

A Decision-Making Model for Predicting Technology Adoption Success

Advanced manufacturing technology (AMT) has the potential to significantly improve manufacturing performance and boost competitiveness in the global market. Investment in AMT remains a promising but potentially risky venture due to the numerous factors that must be considered before the full benefits of implementing a new technology can be realized. To respond to the reported risks and uncertainties, such as those revealed in the recent industrial revolution, it is very important to identify and classify the critical factors that can influence the success of AMT adoption early in the planning stage. Based on an extensive review of relevant literature, 32 critical factors are identified and classified into ten categories in this paper. A new multiple-input single-output (MISO) model is developed by combining the fuzzy Delphi method (FDM) and the fuzzy inference system (FIS) based on the objectives defined. The FDM is used to determine the critical factors, and the FIS addresses the general fuzzy multi-attribute decision-making (MADM) problem in order to evaluate and predict the percentage of AMT adoption success with an existing system. The model is validated using a numerical test bed, and the results show that the model is a proper tool for risk management in AMT implementation.

Rate-Splitting Multiple Access for RIS-Aided Cell-Edge Users With Discrete Phase-Shifts

This letter investigates a reconfigurable intelligent surface (RIS)-aided multiple-input-single-output (MISO) communication system which uses rate-splitting multiple access (RSMA) protocol. A multi-antenna base-station (BS) communicates with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> cell-edge users using RSMA protocol. Each user is assisted with a dedicated RIS. The closed-form expression for the outage probability (OP) is derived considering the discrete and optimal phase-shifts introduced by RIS elements. The interdependent constraints of the threshold and the RSMA factors are derived and analyzed. For getting further insights, the expression for asymptotic OP is derived. Furthermore, the effects of various factors such as number of RIS elements, number of quantization bits, RSMA factors, threshold, etc. are discussed. The correctness of the derived expressions is validated using the Monte-Carlo simulations.

Energy-Efficient Beamforming for Heterogeneous Industrial IoT Networks With Phase and Distortion Noises

The industrial Internet of Things (IIoT) is one of the key applications in 5G heterogeneous networks. To support high energy efficiency (EE) and reliability of IIoT equipment, it is important to design an efficient resource allocation algorithm in dynamic and complex environments. However, most of the studies on 5G heterogeneous IIoT networks did not address the transceiver hardware impairment (HWI) issues (e.g., phase noises, amplifier nonlinearities, and quantization errors) and the corresponding algorithms may not be applicable in practice. To this end, in this article, we investigate a realistic beamforming algorithm in a multicell downlink multiple-input single-output heterogeneous IIoT network by incorporating HWIs in our design. In particular, a beamforming design problem is formulated as a nonconvex optimization problem for maximizing the total EE of all equipment subject to the quality of service constraints of the IIoT equipment in both the macrocell and femtocells and the maximum transmit power constraints of base stations. In light of the intractability of the considered problem, we develop an EE-based iterative beamforming algorithm to tackle the formulated problem by employing the semidefinite relaxation method, Dinkelbach’s method, and the successive convex approximation method. Simulation results show that the proposed algorithm can achieve higher EE and bring less interference power to the macrocell IIoT equipment by comparing it with baseline algorithms.

Joint Beamforming Designs for Active Reconfigurable Intelligent Surface: A Sub-Connected Array Architecture

Reconfigurable intelligent surface (RIS) is regarded as a promising technology with great potential to boost wireless networks. Affected by the “double fading” effect, however, conventional passive RIS cannot bring considerable performance improvement when users are not close enough to RIS. Recently, active RIS is introduced to combat the double fading effect by actively amplifying incident signals with the aid of integrated reflection-type amplifiers. In order to reduce the hardware cost and energy consumption due to massive active components in the conventional fully-connected active RIS, a novel hardware-and-energy efficient sub-connected active RIS architecture has been proposed recently, in which multiple reconfigurable electromagnetic elements are driven by only one amplifier. In this paper, we first develop an improved and accurate signal model for the sub-connected active RIS architecture. Then, we investigate the joint transmit precoding and RIS reflection beamforming (i.e., the reflection phase-shift and amplification coefficients) designs in multiuser multiple-input single-output (MU-MISO) communication systems. Both sum-rate maximization and power minimization problems are solved by leveraging fractional programming (FP), block coordinate descent (BCD), second-order cone programming (SOCP), alternating direction method of multipliers (ADMM), and majorization-minimization (MM) methods. Extensive simulation results verify that compared with the conventional fully-connected structure, the proposed sub-connected active RIS can significantly reduce the hardware cost and power consumption, and achieve great performance improvement when power budget at RIS is limited.

Vector Perturbation Channel Inversion for SWIPT MU-MISO Systems

This letter investigates the employment of vector-perturbation (VP) precoding to convey simultaneously information and energy in multiple-user multiple-input single-output (MU-MISO) downlink channel. We show that the conventional VP in addition to the information capacity benefits that provides to linear channel inversion techniques, it enhances the harvested energy at the receivers due to the extended symbol constellation. To further boost harvesting performance, the proposed modified VP technique (named VP-EH) designs the VP integer offsets in order to maximize the delivered power. The proposed scheme incorporates an integer least square problem to find the closest lattice point to a point which is given by a Rayleigh quotient optimization problem. Finally, a convex combination between conventional VP and VP-EH is proposed to achieve a trade-off between maximizing information or energy. Theoretical and simulations results validate that VP is a promising technique to simultaneously convey information and energy in MU-MISO systems.

Analysis of Comprehensive Multi-Factors on Station Selection for Moon-Based Earth Observation

With the rapid development of Moon exploration, the concept of establishing Moon-based station for Earth observation (MBSEO) has received more and more attention. Compared with the space-borne Earth observation method, the MBSEO can observe Earth with advantages of higher stability, longer period, wider range, better integrity, and consistency. The MBSEO can not only cover the entire Earth disc, but also has good observation of the target area (TA) whose radius is several times that of the Earth radius (e.g., plasma-sphere/magnetosphere). Basically, site selection is a prerequisite for MBSEO. In this paper, the time coverage of TA (TCTA), e.g., the whole Earth disc or Earth-related plasma-sphere and magnetosphere, and the time coverage of sunlight (TCS) without topography are briefly presented to show their distribution. However, the unevenly distributed craters on the near side make TCTA and TCS badly affected by complicated topography, thereby causing those sites with a high selection possibility of a single factor to not necessarily be suitable for other factors. For example, potential sites at the low-middle latitude on the near side might have better TCTA and flat topography, but its TCS might be terrible for MBSEO. In order to evaluate the above factors comprehensively, a multi-factor fuzzy evaluation (MFE) method based on a multiple-input single-output (MISO) model will be utilized in the period of 18.6 nutation years. By using the proposed evaluation method, the sites near the dividing line, e.g., Amundsen, can still have the absolute possibility of exceeding 0.6, which was selected as MBSEO in low acceptability of sunlight. A similar situation exists in other areas with weaker sunlight constraint, e.g., Malapert A, in the case that the absolute selection possibility of areas becomes closer if more sunlight is tolerable. The results indicate that the areas with low thermal environment for radiation protection and relatively flat topography will have more possibility to be selected, and those potential sites unevenly distributed in craters can still be picked out through our proposed method.

Robust Secure Resource Allocation for RIS-Aided SWIPT Communication Systems.

Aiming at the influence of channel uncertainty, user information leakage and harvested energy improvement, this paper proposes a robust resource allocation algorithm for reconfigurable intelligent reflector (RIS) multiple-input single-output systems based on imperfect channel state information. First, considering the legal user minimum secret rate constraint, the base station maximum transmit power constraint and the RIS phase shift constraint with the bounded channel uncertainty, a joint optimization of the base station active beam, energy beam and RIS phase shift is established. A multivariate coupled nonlinear resource allocation problem for matrices is addressed. Then, using S-procedure and alternating optimization methods, the original non-convex problem is transformed into a deterministic convex optimization problem and an alternating optimization algorithm based on continuous convex approximation is proposed. The simulation results show that the proposed algorithm has better fairness harvested energy compared with the traditional robust algorithm.

Long short‐term memory based real‐time monitoring of potato slice drying using image chromatic features

AbstractThe computer vision system provides a better alternative to conventional quality assessment methods during drying because it is rapid, inexpensive, nondestructive, sensitive, and precise. Experiments were conducted for drying of 1‐mm‐thick potato slices at 45, 50, 55, and 60°C. A laboratory‐scale hot air dryer with the provision of installing an image acquisition system was used to visualize the chromatic changes during the drying process. Multiple input single output (MISO) type long short‐term memory (LSTM) network was used to study the time series data. This network has multivariate input data (chromatic attributes of potato slices) to predict single output (moisture content). The optimized network after hyperparameter tuning has an architecture of 86 hidden layers, an LSTM depth of 2, a dropout value of 0.4, and a learning rate of 0.01, providing the highest R of 0.96 and the lowest RMSE of 13.25 × 10−2. During performance evaluation, the R and RMSE values were obtained to be 0.98 and 3.75 × 10−2, 0.97 and 4.29 × 10−2, and 0.98 and 2.67 × 10−2 at 47, 54, and 58°C, respectively.Novelty impact statementThe real‐time monitoring system helps minimize human intervention to assess product quality during drying. This system allows us to comprehend the complexities in the chromatic quality changes in the product while drying. It also finds its usefulness in continuous type dryers where quality monitoring is a serious issue. Furthermore, the same algorithm can be used for multiple operations like cooking, roasting, baking, etc., and various agricultural commodities after adequate training.

Design of Multiple-Input Single-Output System for EEG Signals

Design of Multiple-Input Single-Output System for EEG Signals

Secrecy Energy Efficiency Optimization for Reconfigurable Intelligent Surface-Aided Multiuser MISO Systems

Currently, the reconfigurable intelligent surface (RIS) has been applied to improve the physical layer security in wireless networks. In this paper, we focus on the secure transmission in RIS-aided multiple-input single-output (MISO) systems. Specifically, by assuming that only imperfect channel state information (CSI) of the eavesdropper can be obtained, we investigated the robust secrecy energy efficiency (SEE) optimization via jointly designing the active beamforming (BF), artificial noise (AN) at Alice, and the passive phase shifter at the RIS. The formulated problem is hard to handle due to the complicated secrecy rate expression as well as the infinite constraints introduced by the CSI uncertainties. By utilizing the Taylor expansion, we transformed the fractional programming into a convex problem, while all the constraints are approximated via the successive convex approximation and constrained concave-convex procedure. Then, by using the extended S-Lemma, we transform the infinite constraints into linear matrix inequality, which is convex. Finally, an alternate optimization (AO) algorithm was proposed to solve the reformulated problem. Simulation results demonstrated the performance of the proposed design.

Constellation Design for Energy-Based Noncoherent Massive SIMO Systems Over Correlated Channels

This letter concerns the constellation design problem in energy-based noncoherent massive single-input multiple-output (SIMO) systems over correlated channels. Thanks to the large number of receiving antennas, we approximate the detection error minimization problem by the maximization of the minimum Kullback-Leibler (KL) divergence of the received signal vectors corresponding to different transmitted symbols. However, the max-min KL divergence problem is still difficult to solve. This is because the KL divergence expression involves summations of nonlinear functions of the transmitted signal powers induced by the channel correlation. We then resort to the Szegö’s theorem on large Hermitian Toeplitz matrices to simplify the formulated problem, which subsequently can be optimally solved by a one-dimensional bisection search. Simulation results demonstrate that the constellation designed by our approach outperforms its counterpart without considering the channel correlation, and the performance gain enlarges as the degree of correlation increases.

Accelerated PARAFAC-Based Channel Estimation for Reconfigurable Intelligent Surface-Assisted MISO Systems

To achieve fast and accurate channel estimation of reconfigurable intelligent surface (RIS)-assisted multiple-input single-output (MISO) systems, we propose an accelerated bilinear alternating least squares algorithm (ABALS) based on parallel factor decomposition. Firstly, we build a tensor model of the received signal, and expand it to obtain the unfolded forms of the model. Secondly, we derive the expression of the estimation problem of two channels based on the unfolded forms to transform the problem into a cost function problem. Furthermore, we solve the cost function problem by introducing a simpler iterative optimization constraint and linear interpolation. Finally, we provide a strategy on the receiver design based on the feasibility conditions discussed in this paper, which can guarantee the uniqueness of the channel estimation problem. Simulation results show that the proposed algorithm can obtain a faster estimation speed and less iteration steps than the alternating least squares (ALS) algorithm, and the accuracy of the two algorithms is very close.

An Efficient MMW 3-D Imaging Algorithm for Near-Field MIMO-SAR With Nonuniform Transmitting Array

In this letter, an efficient millimeter-wave (MMW) frequency-domain imaging algorithm is presented for 3-D object reconstruction of the near-field multiple-input–multiple-output synthetic aperture radar (MIMO-SAR) with nonuniform transmitting array. For each single-input–multiple-output (SIMO) case of the MIMO-SAR setup, the precise spectral echo expression is derived by spherical-wave decomposition and fast Fourier transform (FFT) operations. To obtain the linear phase in range direction, the multiorder approximation theory is employed to expand the coupling phases, and thus the target subimage can be reconstructed by utilizing phase compensation, central wavenumber approximation, and inverse FFT. Finally, the fully focused 3-D image for MIMO setup will be realized through accumulating all the SIMO subimages. Compared with the existing representative algorithms, our method avoids complicated interpolation and achieves high-quality fast imaging with only matrix multiplication and a small amount of iteration operations. The experimental results validate the effectiveness of the proposed algorithm.

A Modern VDCCTA Active Element and Its Electronic Application

In this paper, a novel current mode (CM) building block termed Voltage differencing current conveyor transconductance amplifier (VDCCTA) is developed by combining the voltage differencing current conveyor (VDCC) and an operational transconductance amplifier (OTA). This modern active block VDCCTA is extended for applications such as a lossless inductor, filter design, and chaotic circuit design. An active inductor simulator (AIS) without any component matching is designed using the proposed VDCCTA block and a grounded capacitor as a first application that offers flexibility to model grounded positive active inductor (GPAI), grounded negative active inductor (GNAI), and floating positive active inductor (FPAI) circuits. Moreover, the proposed positive active inductor (PAI) can also be translated for multiple input single output (MISO) voltage mode (VM) universal filter with two external passive elements and chaotic circuitry. The characteristics of VDCCTA are verified with the CM multifunction filter, VM band-pass filter, and VM-MISO filter. A complete exercise of this newly reported VDCCTA block is analyzed for their port characteristics validation and the performance parameters using PSPICE simulation. Finally, experimental verification of the proposed AIS is tested to justify the theoretical and simulated results.

Prediction of flavor of Maillard reaction product of beef tallow residue based on artificial neural network.

The beef flavor of beef tallow residue was improved by enzymatic hydrolysis followed by the Maillard reaction, and the flavor could be predicted using an artificial neural network. Five beef tallow residue hydrolysates were prepared using different enzymes. The Flavourzyme and Papain (FP) hydrolysate had low molecular weight peptides and high degree of hydrolysis and free amino acid content. We identified 49 main compounds, including aldehydes, pyrazines, and furan. Furan and pyrazine were the dominant volatile compounds in the five beef tallow residue-derived Maillard reaction products (MRPs), and their profiles and levels in the FP MRPs were high. The FP MRPs had the best sensory characteristics. The artificial neural network analysis revealed that the multiple input single output model had a better performance than the single input single output model, and the prediction accuracy was>90%, indicating that the MRPs sensory evaluation scores could be accurately predicted.

A Novel High-Efficiency Multiple Output Single Input Step-Up Converter with Integration of Luo Network for Electric Vehicle Applications

Concerns about pollution, climate change, limited fossil fuel supplies, and the desire to eliminate energy dependency have sparked a surge in interest in electric vehicles (EVs). EV requirements have resulted in a variety of difficulties and remedies in EV technology. One of them is the use of DC-DC converters to transfer the level of voltage from the battery in an EV to other needed voltage levels. An independent converter for each operating voltage might be used as a remedy. On the other hand, single input multiple output (SIMO) converters can be utilized to decrease costs, reduce switching loss, and thus enhance the system efficiency. In this paper, a nonisolated step-up converter with the integration of the Luo network is proposed for multiple outputs (24 V and 48 V). In electric vehicles, 48 V is utilized for battery backup, while 24 V is utilized for the horns, headlights, telematics, or the microcontroller. The experimental observations of a 36 V, 600 mA, 24 W prototype confirm the theoretic examination and demonstrate the advantages of the proposed converter over other multioutput converters. The STM microcontroller, based on an ARM cortex microprocessor, is linked into the Luo network for making pulses. The proposed converter achieves 94.2% efficiency at full power. The proposed converter’s performance is evaluated through MATLAB/SIMULINK software, and the results are validated experimentally.