Multiple-input Single-output Research Articles

Active RIS vs. Passive RIS: Which Will Prevail in 6G?

As a revolutionary paradigm for controlling wireless channels, reconfigurable intelligent surfaces (RISs) have emerged as a candidate technology for future 6G networks. However, due to the "multiplicative fading" effect, the existing passive RISs only achieve limited capacity gains in many scenarios with strong direct links. In this paper, the concept of active RISs is proposed to overcome this fundamental limitation. Unlike passive RISs that reflect signals without amplification, active RISs can amplify the reflected signals via amplifiers integrated into their elements. To characterize the signal amplification and incorporate the noise introduced by the active components, we develop and verify the signal model of active RISs through the experimental measurements based on a fabricated active RIS element. Based on the verified signal model, we further analyze the asymptotic performance of active RISs to reveal the substantial capacity gain they provide for wireless communications. Finally, we formulate the sum-rate maximization problem for an active RIS aided multi-user multiple-input single-output (MU-MISO) system and a joint transmit beamforming and reflect precoding scheme is proposed to solve this problem. Simulation results show that, in a typical wireless system, passive RISs can realize only a limited sum-rate gain of 22%, while active RISs can achieve a significant sum-rate gain of 130%, thus overcoming the "multiplicative fading" effect.

Analysis and Optimization of Spectral and Energy Efficiency in Underlaid D2D Multi-Cell Massive MISO Over Rician Fading

This paper investigates the uplink spectral efficiency (SE) characterization and energy efficiency (EE) optimization of device-to-device (D2D) communications underlying a multi-cell massive multiple-input single-output (m-MISO) network, assuming that the channels are modeled with Rician fading. First, an analytical expression for the lower-bound of the ergodic capacity of a typical cellular user (CU) is derived with imperfect channel state information in the presence of D2D links’ interference. Then, a closed-form approximate achievable SE expression for a typical D2D pair is derived considering Rician fading between D2D pairs. The asymptotic SE behavior is analyzed in strong line-of-sight (LOS) conditions for CU and D2D pairs. Also, simplified expressions are obtained for the special case of Rayleigh fading. Next, to optimize the total EE, a transmit data power allocation based on the derived rate expressions is formulated. Since the optimization problem has a non-linear and non-convex objective function, it is intractable to be solved straightforwardly. Therefore, we resort to utilizing an iterative algorithm relying on fractional programming. The numerical results show that a stronger LOS component (i.e., larger Rician K-factor) between a typical CU and its serving BS leads to a significant improvement in the system performance, while it has less effect on the D2D network.

FlyReflect: Joint Flying IRS Trajectory and Phase Shift Design Using Deep Reinforcement Learning

Aerial access infrastructures have been considered a compulsory component of the sixth-generation (6G) networks, where airborne vehicles play the role of mobile access points to service ground users (GUs) from the sky. In this scenario, intelligent reflecting surface (IRS) is one of the promising technologies associated with airborne vehicles for coverage extensions and throughput improvements, a.k.a., flying IRS (F-IRS). This study considers a multiuser multiple-input single-output (MISO) F-IRS system, where the F-IRS reflects downlink signals from ground base stations (BSs) to users located at underserved areas where direct communications are unavailable. To achieve the system sum-rate maximization, we proposed a deep reinforcement learning (DRL) algorithm named <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FlyReflect</monospace> to jointly optimize the flying trajectory and IRS phase shift matrix. First, end-to-end communications from a BS to its GUs via the F-IRS are analyzed to identify environmental and operational factors that impact achievable system sum rate. Subsequently, the system is transformed into a DRL model, which is resolvable by the deep deterministic policy gradient (DDPG) algorithm. To improve the action decision accuracy of the DDPG algorithm, we proposed a mapping function to guarantee that all constraints are satisfied regardless of noise additions in the exploration process. Simulation results showed that our proposed algorithm outperforms state-of-the-art algorithms in multiple scenarios.

Design of model-based control strategies for a novel MISO PEM fuel cell control structure.

Voltage control is critical for the performance of proton exchange membrane fuel cells. However, accurately controlling voltage is challenging, specifically during the current variation. The present study proposes a novel multiple-input single-output (MISO) control structure for a proton exchange membrane fuel cell system to improve performance. Also, this study focuses on airflow optimization and hydrogen consumption optimization, as the literature focuses more on airflow optimization for compressor or pump performance. Firstly, using a genetic algorithm optimization technique, the fractional order model is realized from the existing integer order fuel cell model. Then, the proposed control structure aims to control the output cell voltage by regulating the air and hydrogen inlet rates by designing various model-based controllers for integer and fractional order models. The control performance is evaluated for set point tracking, disturbance rejection, inverse response rejection and time delay compensation. The simulation results show that the fractional order system is observed to give better results than the integer order system, with model predictive controller showing the best results for controlling the stack voltage.

Analysis and Implementation of Switched Capacitor-based Multi-Level Inverter for Electric Vehicles Applications

Significant interest has been shown in switched capacitor (SC)-based multi-level inverters (MLIs), which decrease the need for a DC supply and enhance power quality. The common issues with SC-MLIs include an uneven distribution of conducting paths, increased voltage drop across capacitors, the sum of all inverter DC link voltages across the highest voltage rated switches, and a higher total standing voltage (TSV). The purpose of this paper is to create a SC-MLI with less components in order to maintain a constant voltage across the capacitors, to obtain higher voltage gain with fewer parts, fewer conducting routes, lower TSV, and to create a more affordable and effective inverter. The structure of the MLI is created by a cascade interconnection between the number of SC cells. A single input multiple output (SIMO) converter boosts the DC-link voltage over the stable DC voltage of the solar panels using a modified perturb and observe (P&amp;O) method. Additionally, fewer switches in the conduction path and 50 % of the switches operating at normal frequency guarantee a decrease in an overall loss of power in the proposed network. The benefits of the recommended MLI are made clear by comparing them with 17-level MLIs in terms of the number of elements, stress, gain, and cost factor. Detailed experimental results are shown under various transient conditions to show that the 17-level prototype is operationally viable. The total harmonic distortion (THD) is found to be identical and is less than 5 %, which meets IEEE standards.

Performance analysis of RIS-assisted wireless systems with channel aging and spatial correlation

Reconfigurable Intelligent Surfaces (RISs) have caught wide attention for their advantages in dealing with the blocking obstacles in wireless communications. In this paper, we present a detailed analysis of RIS-assisted multiple-input single-output systems taking into account the joint effects of spatial correlation of the RIS elements and channel aging caused by users' relative movements. More specifically, a novel closed-form expression for the Spectrum Efficiency (SE) with maximum ratio transmission precoding is given. Monte Carlo simulation results verify the accuracy of the analytical results. It is proved that the channel aging phenomenon degrades the system performance while the application of a RIS can compensate for the loss, and the longer transmission time results in the more severe effect of channel aging on the system performance. Moreover, the spatial correlation of the RIS elements degrades communication quality and the SE. In addition, increasing the size of the RIS elements can improve the SE.

Identification of MISO Hammerstein system using sparse multiple kernel-based hierarchical mixture prior and variational Bayesian inference

The Hammerstein model is a cascade composition of a static memoryless nonlinear function followed by a linear time-invariant dynamical subsystem, which is capable of modeling a wide range of nonlinear dynamical systems. Model structural parameter selection (including the model order and the nonlinearity order) and sparse representation of the static nonlinear function are two issues that receive increasing interests in Hammerstein system identification. In this paper, a novel Bayesian sparse multiple kernel-based identification method (BSMKM) for multiple-input single-output (MISO) Hammerstein system is proposed to handle those issues, where the basis-function model and the finite impulse response model are used to represent the nonlinear part and the linear part respectively. Firstly, in order to jointly realize the model parameter estimation, the sparse representation of static nonlinear function (the nonlinearity order selection can also be realized indirectly) and the model order selection of linear dynamical system, a hierarchical prior distribution is constructed based on Gaussian scale mixture model and sparse multiple kernel, which can characterize both inter-group sparsity and intra-group correlation structure. Then, a full Bayesian method based on variational Bayesian inference is proposed to estimate all unknown model parameters, including finite impulse response coefficients, hyperparameters and noise variance. Finally, the performance of the proposed BSMKM identification method is evaluated by numerical experiments using both simulation and real data.

Multiple Input-Single Output DC-DC Converters Assessment for Low Power Renewable Sources Integration

This paper presents a comparison of Isolated (Flyback) and non-Isolated (Buck) multiple input-single output (MISO) DC-DC converters. The analysis of DC-DC converters is based on pulsed voltage source cells (PVSC). The modeling of both converter types is detailed through their mathematical models and electrical simulations using Matlab/Simulink and PSIM. The comparison focuses on the sizing parameters, non-ideal output characteristics and efficiency. Results show that the output voltage of the MISO Buck converter exhibits a linear dependence on the duty cycles control signal and has slightly higher efficiency than the Flyback converter. To validate the operation of both converters, a scenario with two inputs (low-power hydroelectric and photovoltaic voltage sources) is considered. The modeling and control of both source systems are detailed and the MISO converter performance response is evaluated under sources changes and efficiency point of view.

An algorithm to reconstruct the constellations based on the superposed character in the Multi-dimensional transmission VLC system

In the Intensity Modulation and Direct Detection (IM-DD) based Multi-dimensional Visible Light Communication (VLC) system, we display different kinds of constellations by using superposed character. An algorithm named Cyclic Delay Diversity (CDD) is used to reduce the superposed signal order at the transmitter, it improves the data rate to 1.6 Gbps with the Bit Error Rate (BER) under the threshold in the Multiple Input Single Output (MISO) VLC system. Although CDD is a common method used in the Physical Downlink Shared Channel (PDSCH) in Long Term Evolution (LTE), it brings an unexpected result in the VLC system. To our acknowledge, this is the first time to discuss the superposed constellations issue detailly and may provide a bran-new idea in the Multiple Input Multiple Output (MIMO)/MISO VLC system or IM-DD system in the following researches.

Energy Efficiency Optimization for MISO-NOMA SWIPT System with Heterogeneous QoS Requirements

This letter solves the energy efficiency optimization problem for the simultaneous wireless information and power transfer (SWIPT) systems with non-orthogonal multiple access (NOMA), multiple input single output (MISO) and power-splitting structures, where each user may have different individual quality of service (QoS) requirements about information and energy. Nonlinear energy harvesting model is used. Alternate optimization approach is adopted to find the solution, which shows a fast convergence behavior. Simulation results show the proposed scheme has higher energy efficiency than existing dual-layer iteration and throughput maximization methods.

Adaptive Modulation for FSO IM/DD Systems With Multiple Transmitters and Receivers

Atmospheric turbulence is a major impairment in free space optical (FSO) communication systems. Since turbulence induced fading exhibits quasi-static characteristics, reliable feedback of channel state information is possible allowing the implementation of adaptive transmission. In this letter, we consider multiple-input single-output (MISO) and single-input multiple-output (SIMO) FSO systems with pulse position modulation (PPM) and pulse amplitude modulation (PAM). We propose an adaptive algorithm where the modulation size/type is adjusted according to the channel fading conditions. We formulate the design of adaptive algorithm to maximize the spectral efficiency under peak and average power constraints while maintaining a targeted value of outage probability. We present extensive Monte Carlo simulations to demonstrate the performance of proposed adaptive scheme over turbulence channels.

Intelligent Reconfigurable Surface-Aided Space-Time Line Code for 6G IoT Systems: A Low-Complexity Approach

Intelligent reconfigurable surfaces (IRS) have attracted much attention from both industry and academia due to their performance improving capability and low complexity for 6G wireless communication systems. In this letter, we introduce an IRS-assisted space-time line code (STLC) technique. The STLC was introduced as a promising technique to acquire the optimal diversity gain in 1×2 single-input multiple-output (SIMO) channel without channel state information at receiver (CSIR). Using the cosine similarity theorem, we propose a novel phase-steering technique for the proposed IRS-assisted STLC technique. We also mathematically characterize the proposed IRS-assisted STLC technique in terms of outage probability and bit-error rate (BER). Based on computer simulations, it is shown that the results of analysis shows well match with the computer simulation results for various communication scenarios.

Asymptotic Analysis of Max-Min Weighted SINR for IRS-Assisted MISO Systems With Hardware Impairments

We focus on the realistic maximization of the uplink minimum signal-to-interference-plus-noise ratio (SINR) of a general multiple-input single-output (MISO) system assisted by an intelligent reflecting surface (IRS) in the large system limit accounting for HIs hardware impairments (HIs). In particular, we introduce the HIs at both the IRS (IRS-HIs) and the additive transceiver HIs (AT-HIs), usually neglected despite their inevitable impact. Specifically, the deterministic equivalent analysis enables the derivation of the asymptotic weighted maximum-minimum SINR with HIs by jointly optimizing the HIs-aware receiver, the transmit power, and the reflecting beamforming matrix (RBM). Notably, we obtain the optimal power allocation and reflecting beamforming matrix with low overhead instead of their frequent necessary computation in IRS-assisted MIMO systems based on the instantaneous channel information. Monte Carlo simulations verify the analytical results which show the insightful interplay among the key parameters and the degradation of the performance due to HIs.

Improved Data-Driven Model-Free Adaptive Damping Controller Design for Interconnected Power Systems With Stochastic Communication Delays

The original model-based wide-area damping control (WADC) is difficult to obtain good damping performance due to the complex structure of interconnected power systems. In this paper, an improved data-driven model-free adaptive control (ID-MFAC) algorithm is proposed to design WADC for interconnected power systems with stochastic communication delays. First, the multiple-input multiple-output power system can be decoupled as multiple single-input single-output subsystems by considering controller interactions and system disturbances. Second, a step-size vector is designed to adjust the pseudo-partial derivative and make the algorithm more flexible by considering both input and output data adequately. Furthermore, an adaptive delay compensator is designed to compensate stochastic communication delays. Last, simulations are conducted to verify that the ID-MFAC algorithm can efficiently suppress multiple inter-area oscillations modes under various stochastic communication delays.

Rate-Splitting Multiple Access for Intelligent Reflecting Surface-Aided Secure Transmission

In this letter, we study a rate-splitting multiple access (RSMA)-based intelligent reflecting surface (IRS)-aided multi-user multiple-input single-output (MISO) secure communication system with a potential eavesdropper (Eve). Aiming to maximize the minimum secrecy rate (SR) among all the legitimate users (LUs), a design problem for jointly optimizing the transmit beamforming with artificial noise (AN), the IRS beamforming, and the secrecy common rate allocation is formulated. Since the design problem is highly non-convex with coupled optimization variables, we develop a computationally efficient algorithm based on the alternating optimization (AO) technique to solve it suboptimally. Numerical results demonstrate that the proposed design can significantly improve the max-min SR over the benchmark schemes without IRS or adopting other multiple access techniques. In particular, employing the RSMA strategy can substantially reduce the required numbers of IRS elements for achieving a target level of secrecy performance compared with the benchmark schemes.

Asymptotic Capacity Maximization for MISO Visible Light Communication Systems with a Liquid Crystal RIS-Based Receiver

Combined with reconfigurable intelligent surfaces (RISs), visible light communications (VLCs) can increase the communication performance to a great degree. However, the research into RIS-aided VLC systems has mainly focused on mirror array-based RISs deployed on the wall while neglecting liquid crystal (LC)-based RISs in VLC receivers. With the development of advanced materials, the LC RIS has been gradually attracting attention from researchers. Inspired by the current research into the LC RIS, the applications of the LC RIS in multiple-input single-output (MISO) VLC systems are investigated in this paper. We formulate an optimization problem with asymptotic capacity maximization as the objective function and the refractive index of the LC RIS as the independent variable. As for this nonconvex optimization problem, we propose the particle swarm optimization (PSO) algorithm to determine the configuration of parameters for the LC RIS. The simulation results indicate that the employment of the LC RIS in VLC receivers can raise the communication performance of the MISO-VLC systems; meanwhile, the proposed algorithm is an effective way to deal with the optimization problems for LC RIS-based MISO-VLC systems when compared with the exhaustive search method and a baseline scheme. The LC RIS is also expected to solve the dead zone problem in traditional VLC systems.

A New Model Reduction Technique for the Simplification and Controller Design of Large-Scale Systems

In this article, a new method for the simplification and controller design for large-scale linear dynamic plants is proposed. This method is applicable for both large-scale single input single output (SISO) and multiple input multiple output (MIMO) models. The diminution procedure is simple and it assurances the stability of the lower-order plant provided that the higher-order system (HOS) is stable. The characteristic equation of the desired system is evaluated by using the stability equation technique and the coefficients of the numerator polynomial are calculated by applying a simple mathematical process as mentioned in the proposed scenario. This algorithm is suggested for circumventing the limitations of the stability equation scheme and preserving its important features such as stability, passivity, etc. The proposed method ensures the retention of stability and static characteristic of the higher-order plant in the reduced model. For validating the accuracy and effectiveness of the proposed technique, it is implemented on the three standard real-time systems. These systems are further used for the comparison of the proposed method with some other popular existing algorithms. By using the proposed lower-order plant, a controller is obtained for the large-scale system with the help of the moment matching technique. The design of the controller is demonstrated and validated by a real-time system taken from the literature.

FIR-SIMO channel order determination by invariant-signal-subspace matching

We present a novel and computationally simple solution to the problem of determining the order of finite impulse response (FIR) single-input multiple-output (SIMO) channel. The solution is applicable to ideal and realistic wireless channels, with both white and colored noise. It is based on a non-asymptotic goodness-of-fit metric, referred to as invariant-signal-subspace matching (ISSM), aimed at matching pairs of invariant-signal-subspaces, created by exploiting the shift-invariance property of the block-Toeplitz data matrix. A pair of projection matrices corresponding to these subspaces is created for every potential FIR-SIMO order, and the order is then determined as that for which this metric is minimized. Simulation results are included, demonstrating the performance of the proposed solution for both ideal and realistic channels, with both white and colored noise.

Waving Effect Characterization for Water-to-Air Optical Wireless Communication

In this paper, we establish and experimentally verify a water-to-air (W2A) visible light communication (VLC) system through dynamic air-water interface. Considering the complexity of waves in real environments, we divide waves into largescale wave and small-scale wave. Monte Carlo simulation and experimental results show that small-scale wave mainly affects the energy distribution of the light spot on the receiving plane and the variation frequency of link gain, while largescale wave mainly affects the coverage of the light spot. In the W2A-VLC system based on light-emitting diode (LED), the statistical characteristics of variation time and link gain are mainly related to the small-scale wave, and the effect of large-scale wave can be treated as slow fading. In order to design a reliable communication system, a large-divergence-angle LED array and avalanche photodiode (APD) array are used under dynamic water surface. We investigate three cases, namely single-input multiple-output (SIMO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO). In the SIMO or MISO systems, the correlation coefficient of channel gain decreases with the inter-receiver or inter-transmitter distance. A significant transmission performance enhancement can be achieved by deploying more transmitters or receivers and increasing the distance between the transmitters or receivers. A MIMO structure can effectively increase the achievable rate. We further establish a W2A-VLC link in a deep wave pool to verify our research in the real environment. The results show that more intensive small-scale wave yields higher bit error rate (BER), and the diversity scheme can improve the transmission stability and decrease BER.

An Isolated Single Input-Multiple Output DC–DC Modular Multilevel Converter for Fast Electric Vehicle Charging

This article proposes an isolated single input-multiple output (SIMO) dc–dc modular multilevel converter (MMC) for fast charging of multiple electric vehicles (EVs). The proposed topology provides galvanic isolation and facilitates a high-voltage conversion ratio from medium voltage direct current (MVDC) to LVDC (EV battery voltage levels) via intermediate medium-frequency transformer. The proposed topology, as compared to conventional MMC, has reduced number of arms, semiconductor devices and has inherent dc fault blocking capability. Operation of the converter with medium frequency reduces the size of passive components present in it. The output voltage waveshape of the converter results in nearly sinusoidal wave being impressed across transformer's primary with very less <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dv/dt</i> . Analysis of the converter in steady state and during fault conditions have been included in this article. The proposed converter is validated in simulation model and scale down laboratory prototype.