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This paper presents a compact multiple-input multiple-output (MIMO) antenna design for 5G cellular applications. The array consists of four identical compact antenna elements capable of providing extensive radiation coverage and diverse functionalities. Each element utilizes a dual-polarized diamond-ring slot resonator, fed by two microstrip feed lines, operating at 3.4 GHz, making it ideal for the 5G band. This paper emphasizes the importance of achieving desirable isolation between adjacent elements and demonstrates simple but effective decoupling techniques. To achieve this, we incorporate parasitic elements, neutralization lines (NL), a defected ground plane, and arrange the radiating elements at varying orientations relative to each other. This antenna provides a bandwidth of 400 MHz (3.15-3.7 GHz), delivering high-gain patterns with minimal ECC/TARC. Experimental measurements confirm the reliability of the MIMO array by implementing it on a smartphone board, which closely matches the expected performance characteristics. [ABSTRACT FROM AUTHOR]

Hyperthermia induces slight temperature increase of 4–8 °C inside the tumor, making it more responsive to radiation and drugs, thereby improving the outcome of the oncological treatment. To verify the level of heat in the tumor and to avoid damage of the healthy tissue, methods for non-invasive temperature monitoring are needed. Temperature estimation by means of microwave imaging is of great interest among the scientific community. In this paper, we present the results of experiments based on ultra-wideband (UWB) M-sequence technology. Our temperature estimation approach uses temperature dependency of tissue dielectric properties and relation of UWB images to the reflection coefficient on the boundary between tissue types. The realistic measurement setup for neck cancer hyperthermia considers three antenna arrangements. Data are processed with Delay and Sum beamforming and Truncated Singular Value Decomposition. Two types of experiments are presented in this paper. In the first experiment, relative permittivity of subsequently replaced tumor mimicking material is estimated, and in the second experiment, real temperature change in the tumor imitate is monitored. The results showed that the presented approach allows for qualitative as well as quantitative permittivity and temperature estimation. The frequency range for temperature estimation, preferable antenna configurations, and limitations of the method are indicated. [ABSTRACT FROM AUTHOR]

Decentralized control systems are frequently employed to tackle control challenges in multi-input multi-output (MIMO) systems. Hence, this paper proposes a decentralized PID controller that relies on frequency domain specifications. This controller is designed to minimize the loop interactions and fulfill the design criteria of the MIMO system. The PID parameters are calculated based on gain and phase margin specifications. Additionally, a first-order plus dead time model is derived for each of the decoupled subsystems. Furthermore, robust stability is analysed using disc margin analysis, which overcomes the constraints of traditional margins. Moreover, the paper determines a secure range of uncertainty for various levels of gain and phase uncertainties. The findings suggest that the proposed controller achieves robust stability over a broader range of margins when compared to alternative control methods. [ABSTRACT FROM AUTHOR]

MIMO (Multiple Input Multiple Output) makes a major contribution to 5G communication systems by increasing network capacity and spectrum efficiency. In 5G, MIMO enables the use of multiple antennas at base stations and user devices, allowing simultaneous sending and receiving of data over multiple paths. This significantly increases data throughput and connection reliability, especially in environments with high user density. In addition, MIMO technology supports the implementation of beamforming, which focuses signals on a specific direction, reduces interference, and improves signal coverage and quality, making it one of the keys to achieving faster and more responsive 5G performance. Therefore, antennas with wide bandwidth, high gain and MIMO performance are crucial for supporting 5G communication systems. This paper proposes a high-performance MIMO microstrip antenna based on a series planar array with 8×2 elements operating at a resonant frequency of 3.5 GHz for 5G communication systems. A spiral stub and a feed inset are proposed to control the reflection coefficient and bandwidth of the antenna while the series planar array is proposed to increase the gain. To support the MIMO communication system, the proposed antenna is separated into two different ports with a certain distance. From the measurement results, the proposed antenna has high performance indicated by a wide bandwidth of 680 MHz (3–3.68 GHz) and a high gain of 17.8 dB at a resonant frequency of 3.5 GHz. In addition, the proposed antenna has high mutual coupling and diversity indicated by ECC and DG of 0.001 and 9.99 dB, respectively. This work provides a solution to design a high-performance microstrip antenna and can be implemented as a receiving antenna for 5G communication systems [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for designing a decentralized control law for higher-order systems using the H ∞ complementary sensitivity function (CSF) framework. Higher-order systems often exhibit complex dynamics and interactions between the variables, and hence, sophisticated control strategies are required to attain the desired performance. The proposed method exploits the robustness properties of the H ∞ CSF to achieve effective decentralized control for higher-order systems. The CSF approach focuses on shaping the sensitivity of the system to disturbances, thereby minimizing the impact on system performance. The decentralized nature of the control law allows for independent control of each subsystem, reducing the complexity associated with higher-order systems. Furthermore, the controller parameters are determined graphically by enforcing the H ∞ robust criterion. The effectiveness of the proposed methodology is demonstrated through simulations on higher-order systems from various domains, including process control and other systems. Comparative evaluations against existing control methods highlight the superiority of the H ∞ CSF-based decentralized control law in terms of robustness and performance. [ABSTRACT FROM AUTHOR]

The coupled systems with numerous interdependent variables pose considerable control and stability issues in commercial chemical processes. These systems exhibit complex interactions, time delays, parameter uncertainties and disturbances, which can lead to poor performance and reduced productivity. Conventional single-loop controllers struggle to effectively manage the interactions between variables, leading to poor disturbance rejection and tracking accuracy. A more robust and efficient control strategy is essential to tackle these limitations. Hence, a robust decentralized PID controller design is proposed to address the shortcomings of coupled industrial chemical processes. The aim is to enhance control system performance by achieving better disturbance rejection and tracking accuracy, thereby improving process efficiency and product quality. The complementary sensitivity function is exploited to attain this, and a novel graphical tuning method is proposed for obtaining optimal PID controller parameters. The use of the H ∞ robust criterion ensures robust stability and minimizes the influence of external disturbances. The proposed approach offers an efficient means to design robust decentralized controllers for complex chemical processes. The simulation results demonstrate the effectiveness of the method compared to existing controllers. Numerically, the proposed controller is able to attain almost a 20 % reduction in integral absolute error and a 30 % decrease in the settling time for all cases compared to existing controllers. The graphical tuning method enables efficient parameter optimization, resulting in faster response times and reduced settling time. This work represents a significant step toward achieving enhanced control system performance and stability in coupled industrial chemical processes. [ABSTRACT FROM AUTHOR]

This study proposes a universal adaptive control algorithm for an unknown multi-input multi-output (MIMO) system using recursive least squares (RLS) and parameter self-tuning. The issue of adjusting the control and system parameters in response to changes in the platform was discussed. The development of a control algorithm that can consistently achieve reliable and robust control performance in various systems is important. This study aimed to develop a control algorithm that can track the reference value for any unknown MIMO system. For the controller design, an nth-order differential error dynamic model was designed, and an RLS with a scale factor was used to estimate the coefficients of the error dynamics. In the current scenario, the numbers of control inputs and error states in the error dynamics were assumed to be equal. It was designed such that the control input is derived based on the Lyapunov stability concept using the estimated coefficients. The scale factor in the RLS and injection term in the control input based on the sliding-mode approach were computed using a self-tuning methodology. The performance of the proposed universal adaptive control algorithm was evaluated using an actual DC motor and CarMaker (version 8.1.1) software tests under various scenarios. [ABSTRACT FROM AUTHOR]

The process of spectrum sensing in cognitive radio (CR) networks plays a critical role as it identifies frequencies that are not utilized, hence saving on bandwidth and energy. For spectrum sensing in CR systems, the design of multi-input multi-output (MIMO) antenna system for a small super-wideband (SWB) diversity antenna system with three band-notches is suggested. Four identical semi-elliptical monopole antennas, positioned perpendicularly with feed lines tapered CWG type, make up a MIMO antenna. Every antenna for the SWB characteristics has a cross-slot carved on the bottom that is comparable to the radiator. The antenna radiator features two connected slits that produce the image of the split ring resonator and a staircase-like slit to ensure that there is no negative impact on SWB. The antenna has a bandwidth ratio of 36:1 and resonates between 1.2 and 43 GHz. Isolation of up to 18dB and envelop correlation coefficient less than 0.01 is implemented within a resonating band for the MIMO antenna that have orthogonally placed antenna elements. At 3.5 GHz, 5.5 GHz, and 8.5 GHz, there is a drop in gain for a maximum gain of 4 dBi offered by the antenna. A small antenna comprising of 52 mm × 52 mm MIMO has been proposed for this research. The proposed antenna provides higher bandwidth ratio, which makes it simple to integrate into modern RF equipment. This SWB, MIMO antenna surpasses those previously discussed in the literature possessing multiple notched bands. Likewise, the three notches of small super-wideband (SWB) are obtained and implemented without incorporating any filter, thus, the antenna design is quite feasible. [ABSTRACT FROM AUTHOR]

This article explores the use of an active disturbance rejection predictive control strategy for local trajectory planning of unmanned ground vehicles (UGVs). The strategy incorporates an extended state observer and a nonlinear feedback control law to handle internal error and environment disturbance. Nonlinear model predictive control is used to address motion planning and nonholonomic constraints. The proposed algorithm improves the accuracy and efficiency of UGV trajectory planning and control. Simulation and experimental results demonstrate the effectiveness of the strategy, and future research will focus on further improvements and practical implementation. [Extracted from the article]

In an effort to make pumped hydropower storage (PHS) technology feasible for regions with a flat topography, recent research shows promising results using a contra-rotating reversible pump-turbine at low-head. In this study, the impact of dual variable speed and inlet valve control is analyzed to evaluate the effect of these three degrees of freedom (DOFs) on the system efficiency and operating range. To this end, analytical models are described to assess pump-turbine performance, conduit losses and electromechanical losses. Methodologically, optimal efficiency maps are computed for every combination of the three DOFs to evaluate individual and combined effects on the overall efficiency. Furthermore, three energy storage cycles are analyzed to further study the performance in realistic use-cases. Key conclusions include an increase in round-trip efficiency by combining variable speed ratio and inlet valve control of 5.6% and 2.0% compared with only variable speed ratio control and variable inlet valve control, respectively. Furthermore, it is shown that using only 1 DOF significantly limits the operating range, with the addition of a variable inlet valve granting a higher impact than a variable speed ratio. Combining inlet valve and speed ratio control leads not only to the highest efficiency, but also the largest operating range, with a maximum round-trip efficiency of 67.5% and an energy storage capacity of 58.6 Wh/m2. The results confirm that exploiting both dual variable speed operation and inlet valve control yields the maximum efficiency and operating range, and is thus the preferred topology for contra-rotating reversible pump-turbines in low-head operation.

This paper proposes a deep learning-based channel estimation method for multiple-input multiple-output (MIMO) systems in spatially correlated channels. To reduce the pilot overhead of pilot symbol-assisted channel estimation, the proposed method utilizes fewer pilot symbols than the number of transmit antennas. Firstly, based on pilot symbols, the estimated partial MIMO channel matrix, consisting of the partial coefficients of the MIMO channel matrix, is obtained by the linear minimum mean square error algorithm. After that, a deep neural network uses the estimated partial MIMO channel matrix as an input and we have the predicted MIMO channel matrix, that corresponds to the channel state information not transmitting pilot symbols. Finally, by aggregating the estimated partial MIMO channel matrix and the predicted MIMO channel matrix, the proposed method can acquire the reconstructed MIMO channel matrix. In simulation results, to show the validity of the proposed method, various performances of the proposed and conventional channel estimation methods were evaluated. Simulation results show that even though the proposed method does not send the pilot symbols for all transmit antennas, it can achieve almost the same bit error rate and improved throughput performances compared with the conventional channel estimation method.

Hyperthermia induces slight temperature increase of 4–8 °C inside the tumor, making it more responsive to radiation and drugs, thereby improving the outcome of the oncological treatment. To verify the level of heat in the tumor and to avoid damage of the healthy tissue, methods for non-invasive temperature monitoring are needed. Temperature estimation by means of microwave imaging is of great interest among the scientific community. In this paper, we present the results of experiments based on ultra-wideband (UWB) M-sequence technology. Our temperature estimation approach uses temperature dependency of tissue dielectric properties and relation of UWB images to the reflection coefficient on the boundary between tissue types. The realistic measurement setup for neck cancer hyperthermia considers three antenna arrangements. Data are processed with Delay and Sum beamforming and Truncated Singular Value Decomposition. Two types of experiments are presented in this paper. In the first experiment, relative permittivity of subsequently replaced tumor mimicking material is estimated, and in the second experiment, real temperature change in the tumor imitate is monitored. The results showed that the presented approach allows for qualitative as well as quantitative permittivity and temperature estimation. The frequency range for temperature estimation, preferable antenna configurations, and limitations of the method are indicated.

For future fifth-generation (5G) smartphones, a high-efficiency multiple-input/multiple-output (MIMO) antenna system capable of operating in Long Term Evolution (LTE) 42/43/46 is suggested. A pair of small microstrip-fed slot antenna and inverted F antenna is part of the single antenna design structure. They are positioned on the longer side of the FR-4 printed circuit board. In an effort to lessen the mutual coupling, two antenna elements have a U-shaped rectangular slot inserted between them. The detailed study of the suggested MIMO system includes measurement of the reflection parameter, analyzing the radiation performance, performing envelope correlation coefficient (ECC) and channel capacity calculations, and analyses of the effects of user's hand in the vicinity of the antenna array. Simulation and measurement results demonstrate the required performance of the proposed design, that is, greater than 80% of total efficiency, isolation >12 dB, and ECC <0.15. The suggested antenna has the benefits of multiband operation, high efficiency, good isolation, and a small footprint. [ABSTRACT FROM AUTHOR]

A Circular Polarization (CP) Multiple Input Multiple Output (MIMO) system was used in this study with additional components for contemporary communication systems developed. There are 4 elements in the model. On the printed circuit board, each element has a dual-fed with two ports positioned at each of the four corners of smart devices (PCB). A Rogers RO3003 substrate with a dielectric structure size of (64.59 × 64.59) mm². geometrical shape 50-Ohm microstrip lines are used to feed the antenna ports. To accomplish polarization and variety properties, microstrip feed lines are positioned orthogonally. According to the paradigm results, the operational frequency for each port was 4.25 GHz, and the system's operating frequency was 4.23 GHz while diversity gains (DG) of the MIMO antennas were about 10, the gain was suitable (around 7 dB), and Less than 0.0001 was the envelope correlation coefficient (ECC). Additionally, the outcomes demonstrate that the MIMO system may operate in a sub-6 band that is ideal for smart device applications. [ABSTRACT FROM AUTHOR]

MIMO (Multiple-Input-Multiple-Output) antenna systems are promising for fifth-generation (5G) networks, offering lower latency and higher data rates. These systems utilize millimeter-wave (mmWave) frequency bands for efficient transmission and reception of multiple data simultaneously, enhancing overall efficiency and performance. This article presents a compact size, wide band tri-circular ring mmWave MIMO antenna with suitable performance characteristics for next-generation communication systems. The MIMO system consists of a tri-circular ring patch with slots on a ground plane. The four elements of the antenna are arranged together in the polarization diversity configuration with overall dimensions of 23×18×0.254 mm3, and designed on a 0.254 mm thin, flexible RO5880 substrate with a relative permittivity of 2.3 using Computer Simulation Technology (CST) 2022. The proposed antenna design shows the impedance bandwidth of 14 GHz with isolation >18 dB throughout the 26-40 GHz resonance band. The obtained gain is 6.6 dBi at 28 GHz with radiation efficiency > 90%. Several MIMO parameters are also investigated, such as Envelope Correlation Coefficient (ECC), Mean Effective Gain (MEG), Diversity Gain (DG), Total Active Reflection Co-efficient (TARC), and Channel Capacity Loss (CCL), and are found to be within the accepted limits for a practical MIMO system. Furthermore, the fabricated MIMO antenna was tested, and the measured results aligned favorably with the simulated results, confirming the suitability of the proposed design. Through the obtained results, the mmWave MIMO antenna is suitable for practical 5G as well as mmWave applications due to its lightweight, simple design, and wideband characteristics, which cover the 5G frequency bands of 26, 28, 32, and 38 GHz.

In the paper, the problem of compensation of external disturbance in multichannel systems with unmeasurable state vector and delay in the control channel is considered. It is assumed that the disturbance has a harmonic form. To solve the problem of estimating the state vector of a system, a full-order observer with Unknown Input Observer is constructed. A new observer of external disturbance is formed on the basis of the state vector estimates produced by this observer. As a result, a system is formed that uses estimates with an extended state vector. For this system, a regulator is constructed that provides compensation of the disturbance. The proposed algorithm guarantees boundedness of all signals in the closed-loop system and asymptotic stability of the output. It does not require identification of parameters of external disturbance. To demonstrate the performance and efficiency of the proposed approach, computer simulation using MATLAB Simulink software environment is performed. The developed algorithm can be effectively applied in systems with external disturbance in the form of sinusoidal signals, including systems exposed to wind, ship systems, motion control systems of robotic complexes of various types, and others.

The flight control system for reusable launch vehicles has to work for an extensive flight envelope ranging from hypersonic to subsonic Mach numbers. Since the plant dynamics are highly nonlinear, time-varying, and coupled, classical controllers are designed for large stability margins about the linearised points. This limits the performance of the classical controller, and the design process is iterative and time-consuming. Hence adaptive controllers are designed to handle such complex systems using a standard quadratic Lyapunov function. The existing parameter update laws of the model reference adaptive control system are not robust to bounded disturbances and unmodelled dynamics. Hence this paper proposes modified controller parameter update laws using a rectangular projection operator and barrier Lyapunov function, ensuring robustness to structured and unstructured uncertainties. The rectangular projection-based control law provides that the controller parameters remain within the specified upper and lower limits, whereas the barrier Lyapunov-based controller maintains the trajectory also within the specified error limit. The effectiveness of the proposed update laws is demonstrated for the automatic landing phase of a reusable launch vehicle. [ABSTRACT FROM AUTHOR]

Since the 1970s various decentralized control methodologies have been developed to deal with the challenge of controlling complex and/or spatially distributed systems with multiple inputs and multiple outputs (MIMO), e.g., chemical plants, power systems, water systems, etc. In general, the use of distributed information and control structures requires the synthesis of control laws in a constrained (decentralized) information structure. The article presents a novel frequency domain robust decentralized controller design method that is appropriate for uncertain dynamic MIMO systems with equal numbers of input and output variables, which consist of interconnected physical subsystems and are given as a set of square transfer function matrices. The main framework of the proposed method provides the Equivalent Subsystems Method (ESM), whereby the overall closed-loop system under a decentralized controller is stable if, and only if, all the individual closed-loop equivalent subsystems are stable. By generating equivalent subsystems for all transfer matrices, which describe the uncertain MIMO system, the individual uncertain equivalent subsystems are obtained as sets of respective frequency responses. Such representation allows the application of the QFT (quantitative feedback theory) approach to independently design local single-input single-output (SISO) robust controllers which constitute the resulting decentralized controller implemented in real subsystems. The designed controller ensures robust stability of the overall closed-loop system and the required performance as specified by the standard QFT performance specification types in both the equivalent subsystems and the overall closed-loop system. Compared to the existing method and references therein, the proposed method reduces the conservatism of the robust stability conditions and enables the exploitation of the benefits by the SISO QFT approach in the independent design of the robust decentralized controller. The developed design procedure is verified and illustrated in a case study on the robust decentralized level controller design of the quadruple tank process. [ABSTRACT FROM AUTHOR]

This paper introduces a novel two-port ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna system with enhanced isolation characteristics. The antenna, designed on a thin 0.787 mm RO5880 substrate, achieves a compact form factor of 52 × 26 mm 2 and offers a wide bandwidth of 9.2 GHz (2.3 GHz to 11.5 GHz) while meeting the VSWR 2:1 criterion. Notably, the proposed antenna demonstrates an impressive increase in isolation, up to 16 dB, through the integration of a shared radiator with small rectangular slots, effectively reducing interference and improving overall performance. Furthermore, a comprehensive analysis of additional MIMO performance parameters, including the envelope correlation coefficient (ECC) and diversity gain, confirms their satisfactory limits, validating the potential of the proposed UWB-MIMO antenna for various UWB applications. The time domain analysis of the UWB antenna is also analyzed, and results are found to be within satisfactory limits. Simulation and measurement results further support the practicality and effectiveness of the antenna design, highlighting its compact size, wide bandwidth, and enhanced isolation characteristics, positioning it as a promising solution for advanced UWB microwave imaging systems. [ABSTRACT FROM AUTHOR]

This study proposes a universal adaptive control algorithm for an unknown multi-input multi-output (MIMO) system using recursive least squares (RLS) and parameter self-tuning. The issue of adjusting the control and system parameters in response to changes in the platform was discussed. The development of a control algorithm that can consistently achieve reliable and robust control performance in various systems is important. This study aimed to develop a control algorithm that can track the reference value for any unknown MIMO system. For the controller design, an nth-order differential error dynamic model was designed, and an RLS with a scale factor was used to estimate the coefficients of the error dynamics. In the current scenario, the numbers of control inputs and error states in the error dynamics were assumed to be equal. It was designed such that the control input is derived based on the Lyapunov stability concept using the estimated coefficients. The scale factor in the RLS and injection term in the control input based on the sliding-mode approach were computed using a self-tuning methodology. The performance of the proposed universal adaptive control algorithm was evaluated using an actual DC motor and CarMaker (version 8.1.1) software tests under various scenarios.

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This paper addresses the problem of controlling turbidity, dissolved oxygen, ammonium‐ion concentration, and water‐temperature to maintain the desired water quality in an intensive aquaculture plant. The research is carried out to fit into the present scenario of intensive aquaculture in India. The plant model along with uncertain parameters are derived using physical laws and the data acquired from an aquaculture pond in Assam, India. A pre‐compensated multi‐variable quantitative feedback theory (QFT)‐based fully populated robust matrix controller is proposed to mitigate the control challenge. A novel method is used to design the pre‐compensator to enhance the diagonal dominance of plant transfer function matrix. The desired robust stability, reference tracking, and sensitivity specifications are fulfilled by the proposed QFT‐based robust controller despite the parametric uncertainty. The effectiveness of the proposed method is validated through numerical simulation. A comparative study against a H∞$$ {H}_{\infty } $$ controller shows that the proposed controller strategy gives a satisfactory performance compared to it. [ABSTRACT FROM AUTHOR]

Summary: In heterogeneous access network, Multiple‐Input Multiple‐Output (MIMO) radio‐over‐fiber (RoF) system is an efficient approach for multiple signal transmission with low cost and complexity. The performance of RoF fronthaul system in MIMO system will be varied with different nonlinear effects. By adjusting various transmission parameters, such as the input signal power or the laser bias current, the nonlinear impacts produced by the RoF system can be reduced. In this paper, a novel algorithm Improved Aquila Optimization (IAO) is proposed to optimize transmission circumstances of MIMO RoF system. It determines the appropriate bias current for both lasers and Radio Frequency (RF) signal power in a short period. The input signals are wavelength multiplexed with Intensity Modulation and Direct Detection (IM/DD) applied. The carrier as well as transmission frequency is governed by the MIMO‐Long‐Term Evolution (LTE) standard. The proposed system is implemented in MATLAB, and the performance is evaluated. The experimental results show that fast convergence and trade‐off between noise and nonlinearity are obtained with varying bandwidth. In the experimental scenario, the maximum Error Vector Magnitude (EVM) of 1.88, 3.14, and signal‐to‐noise ratio (SNR) of 3.204, and 2.698 was attained for both quadrature phase shift keying (QPSK) and quadrature amplitude modulation (QAM) modulation. [Correction added on 24 April 2023, after first online publication: the SNR values were corrected in the preceding sentence.] For 100 iterations, the processing time was reduced to 0.137 s. When compared with the conventional state‐of‐the‐art approaches, the accuracy and computational complexity of the proposed approach are improved. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach based on the copula models for estimating Millimeter-Wave channel parameters with Rician fading in a correlated MIMO system. Even though the use of these waves faces numerous challenges, having an accurate estimation of their parameters would be a crucial notion for the improved performance of this channel. Since the considered system in this paper is a MIMO system with nearby transmitter antennas, the components of the received signals are correlated. However, a general model is not available for this kind of correlation. By taking into account the correlation, this model enables a precise Joint Probability Density Function (JPDF) by employing copula models for the received signals in the antennas. We also obtain more precise channel parameter estimates using this density function. The multi-path fading parameters in a MIMO system and the correlation coefficients between the transmitter and receiver antennas are both presented in this paper. Some simulations are employed to assess the validity and reliability of estimating Millimeter-Wave channel parameters in a MIMO system. [ABSTRACT FROM AUTHOR]

Two-linked robot arm is a popular model in both laboratory and actual industry. This is a MIMO system which has the same number of inputs and outputs. Because of the interactions between variables, normal SISO control algorithms, such as PID algorithm, do not prove their effectiveness in process of operation. In this paper, we propose using a method of sliding algorithm to control two-linked robot tracking expected trajectories. Results of controlling are proved to be successful through Matlab/Simulink.

The principal objective of this work is to optimize the resources of massive MIMO techniques by an application of a neural network algorithm in order to reduce the manufacturing cost of 5G technology within the wireless peripheries of tropical regions. For plenty of annual precipitation in the tropical regions, the radio signals of these areas get attenuated in communicating any message i.e. signal fading occurs. Various diversity techniques have been used for diminishing signal fading in these tropical areas. MIMO technique is a spatial diversity technique used to minimize signal fading. In this paper, 1 × 1 to 256 × 256 MIMO techniques have been designed with the help of MATLAB and Xilinx system generator, and an 8 × 8 MIMO has been implemented in Xilinx Kintex7 FPGA. A CMOS logic technique has been incorporated to optimize the resources of different MIMO techniques, and for this purpose a two-layer feed forward neural network algorithm has been adopted. A comparison of the theoretical values obtained from the design by using both Xilinx system generator and Simulink with the values derived from the design by using CMOS logic gates, has been displayed in this paper. For neural network optimization, three types of training algorithms have been applied.

This paper introduces a nonlinear adaptive controller of unknown nonlinear dynamical systems based on the approximate models using a multi-layer perceptron neural network. The proposal of this study is to employ the structure of the Multi-Layer Perceptron (MLP) model into the NARMA-L2 structure in order to construct a hybrid neural structure that can be used as an identifier model and a nonlinear controller for the MIMO nonlinear systems. The big advantage of the proposed control system is that it doesn't require previous knowledge of the model. Our ultimate goal is to determine the control input using only the values of the input and output. The developed NARMA-L2 neural network model is tuned for its weights employing the backpropagation optimizer algorithm. Nonlinear autoregressive-moving average-L2 (NARMA-L2) neural network controller, based on the inputs and outputs from the nonlinear model, is designed to perform control action on the nonlinear for the attitude control of unmanned aerial vehicles (UAVs) model. Once the system has been modeled efficiently and accurately, the proposed controller is designed by rearranging the generalized submodels. The controller performance is evaluated by simulation conducted on a quadcopter MIMO system, which is characterized by a nonlinear and dynamic behavior. The obtained results show that the NARMA-L2-based neural network achieved good performances in modeling and control. [ABSTRACT FROM AUTHOR]

In this paper, the multiple input and multiple output system (MIMO) is investigated to mitigate the inter-cell interference (ICI) in visible light communication (VLC). The interference due to light from neighbor cell deteriorates the channel capacity of the system. Therefore, a MIMO-based VLC system is employed to optimize the capacity especially in ICI areas of the room. In this paper, the capacity of 2 × 2 , 3 × 3 and 4 × 4 MIMO systems is investigated and compared with the single input and single output (SISO) channel capacity without interference. The channel capacity improves by increasing the order of MIMO array and it deteriorates due to ICI. However, the effects of ICI are more severe at higher signal-to-noise ratio (SNR) especially at high interference areas. Therefore, the order of MIMO array is investigated at different SNRs in interference regions to achieve the interference-free capacity system. Simulation and theoretical results show that ICI is considerably mitigated by using MIMO system. The high SNR 42, 47 and 51.7 dB is achieved in ICI for 2 × 2 , 3 × 3 and 4 × 4 MIMO system, respectively. [ABSTRACT FROM AUTHOR]

In this article, we propose a light weight, low profile Multiple Input Multiple Output (MIMO) antenna system for compact 5th Generation (5G) mmwave devices. Using a RO5880 substrate that is incredibly thin, the suggested antenna is made up of circular rings stacked vertically and horizontally on top of one another. The single element antenna board has dimensions of 12 × 12 × 0.254 mm 3 while the size of the radiating element is 6 × 2 × 0.254 mm 3 (0.56 λ 0 × 0.19 λ 0 × 0.02 λ 0 ). The proposed antenna showed dual band characteristics. The first resonance showed a bandwidth of 10 GHz with a starting frequency of 23 GHz to an ending frequency point of 33 GHz followed by a second resonance bandwidth of 3.25 GHz ranging from 37.75 to 41 GHz, respectively. The proposed antenna is transformed into a four element Linear array system with size of 48 × 12 × 0.254 mm 3 (4.48 λ 0 × 1.12 λ 0 × 0.02 λ 0 ). The isolation levels at both resonance bands were noted to be >20 dB which shows high levels of isolation among radiating elements. The MIMO parameters such as Envelope Correlation Co-efficient (ECC), Mean Effective Gain (MEG) and Diversity Gain (DG) were derived and were found to be in satisfactory limits. The proposed MIMO system model is fabricated and through validation and testing of the prototype, the results were found to be in good agreement with simulations. [ABSTRACT FROM AUTHOR]

In this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control and repetitive mode control methods, and employs a modified inverse model learning law. The classical inverse model learning law is well known to offer fast convergence and high steady-state performance, provided that the secondary path is minimum phase and well known. The proposed modified inverse model learning law employs a spectral factorization trick, which allows one to use the method with nonminimum phase plants of arbitrary order. Moreover, our scheme includes a controller bandwidth limiting mechanism that can be used to tune the disturbance rejection bandwidth and to improve the closed-loop robustness to errors in the model of the secondary path. The algorithm's behavior and performance are verified with computer simulations that demonstrate suppression of electrical transformer noise and include realistic models of the secondary path. The results show high-level selective attenuation and fast convergence. [ABSTRACT FROM AUTHOR]

Millimeter wave is an important core technology of 5G communication,which has a broad development prospect.With the improvement of communication frequency,the influence of weather on signal transmission is increasing,especially in rainfall environment.In order to establish an accurate and effective communication channel model,a three-dimensional millimeter wave MIMO spatial channel model based on 25 GHz,30 GHz and 78 GHz is proposed for the base station mobile communication scena-rio in rainfall environment.In this paper,the geometric and physical characteristics of raindrops are introduced,and then the rain failure engineering model is briefly described.On this basis,the expression of dynamic rain attenuation is proposed.The model considers the non-stationary channel in time and space domain by the line-of-sight distance and non-line-of-sight path of base station and signal receiver,as well as the non-stationary of receiver motion and dynamic scattering cluster.Finally,the channel is theoretically analyzed by birth death process,and the effects of frequency,rainfall,pitch angle and other parameters on the cross-correlation function and channel capacity are deduced.The influence of pitch angle and other parameters on the correlation function and channel capacity is found to be highly fitting with the actual measurement results by comparing with the measured data in the previous literatures.The research has important theoretical and practical significance for the application of wireless communication system in rainfall environment,which extends the research and application of mobile wireless communication channel model.

Microevolutionary system identification was introduced Ergon (2022), with the specific purpose to show that predictions of genetic adaptations to climate change require that environmental reference values are properly defined. The theoretical development was then limited to single-input single-output (SISO) systems, and the simulations used a toy example with spring temperature as input and mean breeding date as output. Generations were assumed to be non-overlapping. Here, the theory is extended to cover multiple-input multiple-output (MIMO) systems, while the simulation example uses two environmental inputs (spring temperature and rainfall) and two adaptive phenotypic outputs (breeding date and breeding habitat). These extended simulations reveal difficulties involved in predictions of genetic adaptations for complex systems based on short data, where the reference environment values are not included.

Multilevel boost converter is a multi-input multi-output nonlinear strongly coupled system. There is a coupling relationship between flying capacitor voltages and output voltage. In this paper, an optimal control method for n + 1-level boost converter based on exact feedback linearization and decoupling is proposed. The flying capacitor voltages and energy function are selected as the output functions to linearize and decouple the original system into n − 1 first-order subsystems and a second-order subsystem. Based on the optimal control theory, flying capacitor voltage balancing controllers are designed for n − 1 first-order subsystems, and an output voltage regulating controller is designed for the second-order subsystem. A five-level boost converter control system is verified by numerical simulation and a three-level boost converter control system is verified by experiment. Simulation and experimental results show that the proposed control strategy has better dynamic regulation performance and stronger robustness than PI decoupling control strategy based on small-signal model. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) technology is one of the key technical approaches to improve the spectrum efficiency of wireless communication. Modern communication systems employ MIMO and high-order quadrature amplitude modulation (QAM) to maximize spectral efficiency. However, with the increase in the number of antennas and modulation orders, it is very challenging to design a low-complexity and high-efficiency MIMO receiver. In recent years, with the rapid development of new technologies such as artificial intelligence, more and more researchers have tried to apply machine learning techniques in the field of communication to break through the performance of traditional communication algorithms. In this paper, we propose a new low-complexity MIMO detection algorithm: an artificial intelligence-assisted expectation propagation (EP) detection algorithm. Neural network models are used to learn and map some of the time-consuming steps in the EP detection algorithm, converting the complex operation process into a few matrix multiplication operations in order to reduce the complexity of the detection algorithm. It is verified that the method proposed in this paper can approximate the performance of the original EP detection algorithm with reduced complexity and is applicable in different scenarios. [ABSTRACT FROM AUTHOR]

The principal objective of this work is to optimize the resources of massive MIMO techniques by an application of a neural network algorithm in order to reduce the manufacturing cost of 5G technology within the wireless peripheries of tropical regions. For plenty of annual precipitation in the tropical regions, the radio signals of these areas get attenuated in communicating any message i.e. signal fading occurs. Various diversity techniques have been used for diminishing signal fading in these tropical areas. MIMO technique is a spatial diversity technique used to minimize signal fading. In this paper, 1 × 1 to 256 × 256 MIMO techniques have been designed with the help of MATLAB and Xilinx system generator, and an 8 × 8 MIMO has been implemented in Xilinx Kintex7 FPGA. A CMOS logic technique has been incorporated to optimize the resources of different MIMO techniques, and for this purpose a two-layer feed forward neural network algorithm has been adopted. A comparison of the theoretical values obtained from the design by using both Xilinx system generator and Simulink with the values derived from the design by using CMOS logic gates, has been displayed in this paper. For neural network optimization, three types of training algorithms have been applied. [ABSTRACT FROM AUTHOR]

Deep learning can improve the effect of signal detection by extracting the inherent characteristics of wireless communication data.To solve the tradeoff between the performance and complexity of MIMO system signal detection, an end-to-end MIMO system signal detection scheme based on deep learning was proposed.The encoder and the decoder based on residual deep neural network replace the transmitter and the receiver of the wireless communication system respectively, and they were trained in an end-to-end manner as a whole.Firstly, the features of the input data were extracted by encoder, then the communication model was established and was sent to the zero forcing detector for preliminary detection.Finally, the detection signal was reconstructed through the decoder.Simulation results show that the proposed detection scheme is superior to the same type of algorithm, and the detection performance is significantly better than that of the MMSE detection algorithm at the expense of a certain time complexity.

This paper introduces a novel two-port ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna system with enhanced isolation characteristics. The antenna, designed on a thin 0.787 mm RO5880 substrate, achieves a compact form factor of 52 × 26 mm2 and offers a wide bandwidth of 9.2 GHz (2.3 GHz to 11.5 GHz) while meeting the VSWR 2:1 criterion. Notably, the proposed antenna demonstrates an impressive increase in isolation, up to 16 dB, through the integration of a shared radiator with small rectangular slots, effectively reducing interference and improving overall performance. Furthermore, a comprehensive analysis of additional MIMO performance parameters, including the envelope correlation coefficient (ECC) and diversity gain, confirms their satisfactory limits, validating the potential of the proposed UWB-MIMO antenna for various UWB applications. The time domain analysis of the UWB antenna is also analyzed, and results are found to be within satisfactory limits. Simulation and measurement results further support the practicality and effectiveness of the antenna design, highlighting its compact size, wide bandwidth, and enhanced isolation characteristics, positioning it as a promising solution for advanced UWB microwave imaging systems.

This paper aims to develop a fractional control approach for quadrotor trajectory tracking. A fractional-order integrator (PI $^{\lambda} $ ) with a feedback derivative scheme is designed to control each state of the MIMO system. The designed feedback controller stabilizes the initially unstable decoupled states and widens the stability, while PI $^{\lambda} $ provides precise trajectory tracking capabilities. After a successful simulation study, the new PI $^{\lambda} $ -D controller is implemented in the hardware environment. The various performance and load disturbance analyses reveal the effectiveness of the proposed scheme compared with the classical PD/PID controllers. The real-time study also shows that this scheme is a simple yet robust solution.