Multi-input Single-output System Research Articles

Demonstration of D-band 1×2 SIMO millimeter-wave wireless delivery over 1.2 km employing MRC technology

We experimentally demonstrate the transmission of 20-Gbaud QPSK millimeter-wave signals within a 1.2-km wireless range at 128-GHz using constant-modulus-algorithm (CMA) and the maximum ratio combining (MRC) technology with over 2.2-dB gain in a photonics-assisted millimeter wave (MMW) 1 × 2 Single Input Multi Output (SIMO) communication system. MRC is applied for SIMO signal merging which leads to Signal to Noise Ratio (SNR) enhancement and significant Bit Error Rate (BER) reduction. The comparison which is performed for Single Input Single Output (SISO) and SIMO system, demonstrates the BER improvement. To the best of our knowledge, this is the first experimental demonstration of high gain in a D-band MMW 1 × 2 SIMO system by using these technologies.

A Wireless Power Transfer Mattress Based System for Perpetually Operating Physiological Monitoring Wearables.

This article presents a novel wireless power mattress-based system architecture tailored to guarantee continuous energy for in-home environment healthcare wearables intended to be used in the context of patients who would benefit from long-term monitoring of specific physiological biomarkers. The design demonstrates that it is possible to transfer over 20 mW at a primary-secondary distance of 20.7 cm, whilst still keeping within all FCC/ICNIRP safety regulations, using the proposed simplified beamforming-controlled power transfer multi-input single-output system. Compared with other beamforming-controlled based works, the proposed design used non-coupling coil arrays, significantly reducing the algorithmic complexity. An on-chip wireless power charger system was also designed to provide high-efficiency power storage (89.3% power conversion efficiency and 83.9% power charge efficiency), guaranteeing wearables can continuously maintain their functionality. In contrast with conventional NiMh chargers, this work proposes a trimming function that makes it compatible with batteries of varying capacities. It also employs a four-stage charge loop to ensure safety and sustainability during the charging process. Overall, this work shows that by relying on wireless power transfer, it is, in principle, possible to create a safe wearable that could enable continuous monitoring of certain healthcare biomarkers with little or zero maintenance burden for the patients or carers.

Novel integrated guidance and control design for a three-stage satellite carrier using model-free adaptive control

A model-free adaptive control is proposed for suboptimal guidance correction and control of a prototypical three-stage satellite carrier. For this sake, we consider a nominal guidance for the model of the system and design the adaptive control for a single-input multi-output system exposed to wind disturbance and measurement noise in the rates of inputs and outputs. Then, subsequent to the guidance correction, a differentiation model of the system is estimated and the control policy is realized under some profitable performance constraints to set the satellite in a desirable circular orbit. The simulation results readily reveal the efficiency of the proposed method and its robustness to uncertainties in the system.

An enhanced 2-D color space diversity using RGB-LED overlapping for optical camera communication

In this paper, an enhanced two-dimension (2-D) color space diversity technique using red, green, and blue light emitting diode (RGB LED) overlapping is proposed and investigated experimentally to improve the system reliability for optical camera communication (OCC). The transmitter adopts an 8-color shift keying (8-CSK) modulation scheme with two RGB LED overlapping. The receiver uses a camera to form a multi-input single-output system to improve capacity. Different mapping methods are proposed and compared in 2-D YCbCr and CIElab color space to avoid the influence of brightness in conventional 3-D RGB space. Besides, clustering-based demapping is applied in the OCC system to transfer the color information into a data stream. The experimental results show that the mapping scheme with the maximum Euclidean distance in 2-D YCbCr color space has the best bit error rate (BER) performance. Compared with the conventional 3-D RGB color space, the proposed enhanced 2-D YCbCr color space diversity has a higher resolution to signal, which can realize 1.46 dB Q-factor improvement at an illumination of 660 lux. In addition, it can achieve a net data rate of 11.52 kb/s and maintain a 7% forward error correction (FEC) requirement even under low illumination. It is verified that the proposed scheme is a potential application for capacity and performance improvement.

Optimal FOPI-FOPD controller design for rotary inverted pendulum system using grey wolves’ optimization technique

The rotary inverted pendulum (RIP) has been used in various control application areas. This system can be represented as two degree of freedom (2-DOF), consisting of a rotating arm and rotating pendulum rod. RIP is an excellent example of designing a single-input multi-output (SIMO) system. Due to unstable RIP system dynamics, and its nonlinear model, multiple control techniques have been used to control this system. This paper uses integer and fractional order proportional integral-proportional derivative (PI-PD) controllers to stabilize the pendulum in the vertical direction. Constrained optimization approaches, such as the grey wolf optimization (GWO) methodology, are utilized to estimate the parametric values of the controllers. The simulation results showed that the fractional order PI-PD controller outperforms the integer order PI-PD controller with and without disturbance signal existence. A multiple results comparison has illustrated the superiority of fractional order controller over a previous work.

UKF-Based Channel Tracking Method for IRS-Aided mmWave MISO Systems

In this paper, we propose an unscented Kalman filtering (UKF)-based method to track the channel parameters of the intelligent reflecting surface (IRS) aided millimeter wave (mmWave) multi-input single-output (MISO) systems. To minimize the mean squared error (MSE) of the tracking parameters, the beamforming vector of the base station (BS) and the reflecting vector of the IRS are designed iteratively, considering the transmit power constraint of the BS and the unit module constraint of the IRS. The resulting sub-problems can be transformed into quadratic constraint quadratic problems (QCQPs), which are solved by the semidefinite relaxation (SDR) method and Gaussian randomization. Simulation results demonstrate that the proposed method outperforms existing benchmark methods.

Audio SIMO system based on visible light communication using cavity LEDs

The necessity for access to a high data rate has been the motivation behind expanding new technologies. The increasing of wireless devices has caused the radio wave spectrum to become congested. Additionally, radio waves cannot be used in EMI-vulnerable places. Hence, the interest in visible light communication (VLC) offers real alternatives to radio-based communications. This paper focuses on the use of visible light as a data communication medium and introduces a designed audio SIMO (Single-Input-Multi-Output) data transmission system from point to multipoint to demonstrate the functionality of the VLC system in audio transmission through modulated LEDs light. The system is made up of the transmitting unit and multi-receiving units. The transmitting unit consists of three stages: audio in, preamplifier, and white LEDs array that transmits the data using the ON-OFF keying (OOK) modulation technique to all receivers. On the other hand, the receiving unit consists of three receivers that have different photodetectors aspects with fixed distances separation between them. The line of sight (LOS) communication between transmitter and receivers for the purpose to transfer audio data has been employed. Based on the LOS link, simulation and experimental analysis have been done in multiple semi-angles for studying the output performance of receivers and the characteristics of the white LEDs such as luminous intensity and received power at 20,45 and 70 semi-angle at half-power through MATLAB® software.

Data-Driven Modelling of Soil Moisture Dynamics for Smart Irrigation Scheduling

In the face of increasing water scarcity and uncertainties of climate change, improving crop water use efficiency and productivity, while minimizing negative environmental impacts, is becoming crucial to meet the surging global food demand. Smart irrigation has a potential of improving water use efficiency in precision agriculture especially when efficient irrigation control strategies are adopted. Conventionally, irrigation systems rely on heuristic methods to schedule irrigation which either leads to over-irrigation or under-irrigation. This influences the crop physiological characteristics as well as the water use efficiency. To tackle this menace, model-based irrigation management has been overemphasized. A closed-loop irrigation control strategy relies on a mathematical model of the system for irrigation scheduling decisions. In this study, a data-driven approach was used to learn soil moisture dynamics from a drip irrigated tomato in an open field agricultural system. A total number of 9674 data samples were collected using an ATMOS41 weather station, TERROS 12 soil moisture sensor and a YFS-201 flow sensor for crop evapotranspiration and precipitation, soil moisture and irrigation volumes respectively. Data driven modelling was then performed using the system identification toolbox in a MATLAB environment. The model formulation was a multi-input single-output (MISO) system with reference evapotranspiration, irrigation and rainfall as inputs and soil moisture as the output. Different model structures including transfer functions, state space models, polynomial models and ARX models were evaluated. Model performance was evaluated using the mean square error (MSE), final prediction error (FPE) and estimated fit of the model approaches. Simulation results indicate that the soil moisture dynamics model provides a satisfactory approximation of the process dynamics with a state space model giving an estimated fit of 97.04 %, MSE and FPE of 1.74×10−7 and 1.75×10−7 respectively. This model will be used to design a model predictive controller for smart irrigation scheduling in open field environmental conditions.

Zone-wise surrogate modelling (ZSM) of univariate systems

Many complex systems display distinctly different behaviors across regions, zones, or sub-domains. A single surrogate may not suffice in modelling such systems. A better approach would be to identify the various zones and model them individually. In this work, we propose a zone-wise surrogate modelling (ZSM) algorithm to identify various zones in a system's input domain based on a user-specified acceptable goodness of fit and recommend the best surrogate for each identified zone from a library of potential surrogates. We have assessed ZSM on ten case studies involving complex 1-D functions and compared its modelling performance against some non-linear and piecewise models. We also show how ZSM can help in global optimization using five complex multimodal functions and found that a ZSM-based approach successfully identifies the true global optima of these functions. In future, we aim to extend ZSM for the modelling and optimization of complex multi-input single-output (MISO) systems.

The data-filtering based bias compensation recursive least squares identification for multi-input single-output systems with colored noises

For the multi-input single-output (MISO) system corrupted by colored noise, we transform the original system model into a new MISO output error model with white noise through data filtering technology. Based on the newly obtained model and the bias compensation principle, a novel data filtering-based bias compensation recursive least squares (BCRLS) identification algorithm is developed for identifying the parameters of the MISO system with colored noise disturbance. Unlike the exiting BCRLS method for the MISO system (see, in Section 3), without computing the complicated noise correlation functions, still the proposed method can achieve the unbiased parameters estimation of the MISO system in the case of colored process noises. The proposed algorithm simplifies the implementation of and further expands the application scope of the existing BCRLS method. Three numerical examples clearly illustrate the validity of and the good performances of the proposed method, including its superiority over the BCRLS method and so on.

Joint Beamforming Design for Intelligent Omni Surface Assisted Wireless Communication Systems

Intelligent reflecting surface (IRS) has been widely considered as one of the key enabling techniques for future wireless communication networks owing to its ability of dynamically controlling the phase shift of reflected electromagnetic (EM) waves to construct a favorable propagation environment. While IRS only focuses on signal reflection, the recently emerged innovative concept of intelligent omni-surface (IOS) can provide the dual functionality of manipulating reflecting and transmitting signals. Thus, IOS is a new paradigm for achieving ubiquitous wireless communications. In this paper, we consider an IOS-assisted multi-user multi-input single-output (MU-MISO) system where the IOS utilizes its reflective and transmissive properties to enhance the MU-MISO transmission. Both power minimization and sum-rate maximization problems are solved by exploiting the second-order cone programming (SOCP), Riemannian manifold, weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results verify the advancements of the IOS for wireless systems and illustrate the significant performance improvement of our proposed joint transmit beamforming, reflecting and transmitting phase-shift, and IOS energy division design algorithms. Compared with conventional IRS, IOS can significantly extend the communication coverage, enhance the strength of received signals, and improve the quality of communication links.

Adaptive-PID Experimental STM32F4 Controller for Rotary Inverted Pendulum

Rotary inverted pendulum (RIP) is a classical model of control engineering. Paper deals with a PID-adaptive structure which is based on structure of neuron to train Kp, Ki, Kd through operation. In simulation, our adaptive controller is proven to work in larger range than classical PID controller. Through experimental model using STM32F4, we prove vibration of system under adaptive-PID is smaller than under classical PID structure. Then, combination of neuron network (NN) and PID control can be used as simple structure for single-input multi output (SIMO) systems which are similar to RIP.

Dictionary Learning-Based Channel Estimation for RIS-Aided MISO Communications

In this letter, we study the channel estimation problem for the reconfigurable intelligent surface (RIS)-aided multi-input single-output (MISO) system. By exploiting the channel sparsity, compressive sensing (CS) based sparse channel estimators can be applied to the system to reduce the training overhead. However, these existing sparse channel estimators adopt predefined dictionaries when formulating the sparse matrix recovery problem, which will cause grid mismatch issues and estimation performance degradation. Hence, in this letter, we formulate the channel estimation problem as a joint dictionary parameter learning and sparse signal recovery problem, in which the dictionary parameter can be optimized to adapt to the channel measurements, thereby improving the robustness of sparse channel representation and estimation performance. Then, we propose an iterative re-weighted algorithm to solve this non-convex problem efficiently. Simulation results show that the proposed algorithm outperforms other benchmark schemes significantly.

Robust identification of multiple-input single-output system response for efficient pickup noise removal from tokamak diagnostics.

Electromagnetic pickup noise in the tokamak environment imposes an imminent challenge for measuring weak diagnostic photocurrents in the nA range. The diagnostic signal can be contaminated by an unknown mixture of crosstalk signals from coils powered by currents in the kA range. To address this issue, an algorithm for robust identification of linear multi-input single-output (MISO) systems has been developed. The MISO model describes the dynamic relationship between measured signals from power sources and observed signals in the diagnostic and allows for a precise subtraction of the noise component. The proposed method was tested on experimental diagnostic data from the DIII-D tokamak, and it has reduced noise by up to 20 dB in the 1-20kHz range.

Data mining and machine learning improve gravitational-wave detector sensitivity

Application of data mining and machine learning techniques can significantly improve the sensitivity of current interferometric gravitational-wave detectors. Such instruments are complex multi-input single-output systems, with close-to-linear dynamics and hundreds of active feedback control loops. We show how the application of brute-force data-mining techniques allows us to discover correlations between auxiliary monitoring channels and the main gravitational-wave output channel. We also discuss the result of the application of a parametric and time-domain noise subtraction algorithm, that allows a significant improvement of the detector sensitivity at frequencies below 30 Hz.

BIOS: An Omni RIS for Independent Reflection and Refraction Beamforming

As an important member of reconfigurable intelligent surfaces (RISs), intelligent omni-surface (IOS) has attracted increasing attention recently due to its ability of simultaneously serving user equipments (UEs) on both sides of the metasurface. However, in practical implementation, the phase shifts of the IOS must be shared for both reflection and refraction signals, which inevitably leads to coupled reflection and refraction beams. To address this issue, in this letter, we propose an innovative bilayer-IOS (BIOS) structure to achieve flexible reflection and refraction beamforming. Thanks to the deployment of two neighboring IOSs, the BIOS can almost independently control the reflection and refraction beams for UEs on both sides of it. We apply the proposed BIOS in a multi-user multi-input single-output system, formulate the joint base station precoding and BIOS passive beamforming optimization problem aiming at maximizing the system spectral efficiency, and solve it via a weighted mean square error minimization design approach. Simulation results validate the superiority of BIOS over the conventional RISs.

Proportional Tracking Control of Positive Linear Systems

This letter considers the reference tracking of positive linear systems via a proportional controller, which remains an open problem. Through using a virtual reference method in state-space models, optimal tracking performance is guaranteed for single-input multi-output (SIMO) systems via a bisection method. The proportional tracking for multi-input multi-output (MIMO) systems is reformulated as a bi-convex programming problem and a convergence-guaranteed algorithm is developed through using iterative linear matrix inequalities. Numerical simulations are provided to verify the proposed results.

Sensitivity-based model-free adaptive displacement and velocity control algorithms for unknown single-input multi-output systems with recursive least squares

Sensitivity-based model-free adaptive displacement and velocity control algorithms for unknown single-input multi-output systems with recursive least squares

Reconfigurable Intelligent Surface-Assisted Multi-Cell MISO Communication Systems Exploiting Statistical CSI

In this letter, we investigate the reconfigurable intelligent surface (RIS) assisted multi-cell downlink multi-input single-output system under the assumption of only statistical channel state information at the base stations and RIS. Firstly, a closed-form ergodic weighted sum rate approximation is obtained. Then, based on this approximation, we propose an approximate optimal joint beamforming vectors and RIS phase shift matrix design algorithm utilizing the fractional programming and complex circle manifold. Simulation results show that the proposed low-complexity algorithm performs well.

A generalized sensitivity analysis method based on variance and covariance decomposition of summatory functions for multi-input multi-output systems

Sensitivity analysis is a useful means to quantify the impact of a set of input variables on an output response. However, many traditional sensitivity analysis methods are applicable only to multi-input single-output (MISO) systems and are powerless for multi-input multi-output (MIMO) systems. This paper presents a global sensitivity analysis method based on variance and covariance decomposition (VCD-GSA) of summatory functions for MIMO systems. For a MIMO system with n input variables and m output responses, a set of summatory functions can be constructed by the addition and subtraction of any two output response functions. Each output response function is represented using this set of summatory functions. The variances and covariances of all the output responses are obtained by the integral calculation of the high-dimensional model representations(HDMRs) of these summatory functions. We define the total fluctuation by the sum of the variances and covariances on multiple responses, and the partial fluctuations by the sum of partial variances of a series of summatory functions. Subsequently, we define the s-order sensitivity index of the MIMO system by the ratio of the partial fluctuation on s-order function terms in HDMRs and total fluctuation. The variable sensitivity index is the sum of all of the s-order sensitivity indices, including the contribution of the input variable. The proposed VCD-GSA method is suitable for a uniform or Gaussian distribution. It is also suitable for some complex problems involving variables with correlation. Several numerical examples and engineering applications demonstrate the advantage and practicality of the proposed VCD-GSA method.