Improved Likelihood Probability in MIMO Systems Using One-Bit ADCs.

This study considers an improved likelihood probability in multi-input multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs). MIMO systems using one-bit ADCs are known to exhibit from performance degradation because of inaccurate likelihood probabilities. To overcome this degradation, the proposed method leverages the detected symbols to estimate the true likelihood probability by combining the initial likelihood probability. An optimization problem is formulated to minimize the mean-squared error between the true and combined likelihood probabilities, and a solution is derived using the least-squares method. Simulation results show that the proposed method obtains a signal-to-noise gain of approximately 0.3 dB to achieve a frame error rate of 10-1 compared to conventional methods. This improvement in performance is attributed to the enhanced reliability of the likelihood probability.

A Left-Null-Space-Based Massive Access Method for Cell-Free Massive MIMO IoT Systems.

Cell-free massive multiple-input multiple-output (MIMO) is a promising technology for the Internet of Things (IoT) because it can increase connectivity and provide considerable energy efficiency (EE) and spectral efficiency (SE). However, pilot contamination caused by pilot reuse severely limits the performance of the system. In this paper, we propose a left-null-space-based massive access method that can significantly reduce interference among users. The proposed method includes three stages: initial orthogonal access, left-null-space-based opportunistic access and data detection of all accessed users. The simulation results show that the proposed method can achieve much higher spectral efficiency than the existing massive access methods.

Compact Sub 6 GHz Slot Multiantenna System for 5G Laptops.

A sub 6 GHz dual-band closed-slot multiantenna system for 5G laptops is proposed in this paper. It was installed in a clearance space, with dimensions og 217 × 3 mm2 and 1 mm away from the upper edge of the screen ground plane. The dimensions of the clearance space were the same as those of a multisystem consisting of six antennas. The dimensions of the single closed-slot antenna were 32 × 3 mm2 (0.368 λ × 0.034 λ, where λ equals the free-space wavelength of 3450 MHz. The antenna was coupled to an asymmetric T-shaped feed-in section equipped with a chip capacitor for exciting one-half and full wavelength resonance modes of the closed-slot to encompass sub 6 GHz 3300-3600 MHz and 4800-5000 MHz dual-band operations. The design of the antenna features a long and straight slot to generate the high-order mode of the closed slot in the high-frequency (4800-5000 MHz) band (not the low-frequency (3300-3600 MHz) multiplier band). Its structure is simple, and the width of its slot is only 3 mm. The antennas were arranged to be 5 mm apart in the same direction and in parallel to form a six-antenna system in order to utilize the weak electric fields located at the two closed ends of the closed-slot structure when the closed slot was excited. It showed excellent envelope correlation coefficients (ECCs) and isolation performance without the installation of isolation elements. The measured fractional bandwidth of the antenna was 10.15% and 6.73% at the center frequencies of 3450 MHz and 4900 MHz, respectively. Its measured isolation was always over 10 dB, and the efficiency was between 46% and 76%. The ECCs of the system calculated from the measured complex E-field radiation pattern were all below 0.2, which means that it is ideal for use in laptop devices with a high screen-to-body ratio and a metal back cover.

Multi-input multi-output temporal convolutional network for predicting the long-term water quality of ocean ranches.

The prediction of water quality parameters is of great significance to the control of marine environments and provides a scientific decision-making basis for maintaining the stability of water environments and ensuring the normal survival and growth of marine aquatic products. However, the water quality in ocean ranches is affected by the complex, dynamic, and changeable environments of open water, which have complex nonlinear relationships, poor accuracy, high time complexity, and poor long-term predictability. Therefore, in this paper, a multi-input multi-output end-to-end prediction model based on a temporal convolutional network (MIMO-TCN) is proposed to predict water quality. A ConvNeXt module and TCN module were used as the model encoder and decoder, respectively. ConvNeXt was used to extract the features of the input data, and the TCN used the extracted feature data to achieve improved prediction accuracy. The model adds skip connections between its modules to solve the gradient disappearance problem as the number of network layers increases. To prove the effectiveness of the proposed method, a model robustness and prediction ability evaluation was conducted in this paper based on the dissolved oxygen in multiple ocean pasture validation samples. Compared with other learning models, the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) of the MIMO-TCN prediction results were reduced by 60.77%, 30.88%, and 52.45% on average, respectively, and the R2 improved by 6.07% on average over those of other models. The experimental results show that the proposed method has higher forecasting accuracy than competing approaches.

Regional differences of individual and allocation efficiencies of health resources in China.

Background: The existing health resources and services are difficult to meet the needs of rapid economic development and the aging population in China. This paper evaluates the regional differences of individual and allocation efficiencies of health resources in China to explore ways to change the current situation. Methods: The models of single-input single-output efficiency (SISOE), single-input multi-output efficiency (SIMOE), multi-input single-output efficiency (MISOE), and multi-input multi-output efficiency (MIMOE) were developed to calculate the individual and allocation efficiencies of health resources of China in this study. Results: It was found that the efficiencies of the number of health institutions (NHI) in the eastern and western regions of China were relatively close, with values of 0.61 and 0.59, respectively, significantly higher than 0.49 in the middle region. The efficiencies of the number of health personnel (NHP) in the eastern, middle, and western regions were closer, with values of 0.77, 0.75, and 0.79, respectively. The efficiencies of the number of health institution beds (NHIB) in the eastern and western regions were very close, with values of 0.79 and 0.78, respectively, while that in the middle region was 0.72. The efficiencies of the total health expenditure (THE) were 0.72, 0.76, and 0.79 in the east, middle, and western regions, respectively. The efficiencies of the number of diagnosis and treatment persons (NDTP) were 0.81, 0.70, and 0.71 in the eastern, middle, and western regions, respectively, while the efficiencies of the number of inpatients (NI) were 0.75, 0.79, and 0.81, respectively. The efficiencies of the utilization rate of beds (URB) and the average days of hospitalization (ADH) in the three regions were below 0.51. The health resources allocation efficiencies (HRAEs) were 0.86, 0.83, and 0.87 in the eastern, middle, and western regions, respectively. Conclusion: There were obvious regional differences in HRAE in China with the situation of "Middle Collapse." The main direct reason for the low HRAE in the middle region was the lower efficiencies of NHI, NHIB, URB, and ADH. It revealed that there was relatively blind expansion of health institutions and beds with lower health service quality in the middle region. Governments should make strategic adjustments to public health resources and increase the investment in medical technology and manpower in the middle region. Hospitals in the eastern region should strengthen inter-regional medical and health technical cooperation with partners in the middle region by establishing a tele-medical network. The models of SISOE, SIMOE, MISOE, and MIMOE put forward in this study are simple, reasonable, and useful for resource efficiency analysis, which makes it convenient to adopt targeted measures to upgrade the efficiency of resource allocation. This study provides a new perspective and method to understand the mechanism of regional differences in China's health resource allocation efficiency.

Efficient MIMO Configuration for Bi-Directional Vertical FSO Link with Multiple Beam Induced Pointing Error.

We proposed the statistical misalignment model and the power-efficient configuration of transceivers for bi-directional multi-input and multi-output (MIMO) based vertical free space optical (FSO) links. Spatial diversity based MIMO FSO systems could be used to mitigate atmospheric fading issues. However, the increased number of channels can cause additional pointing error in pointing, acquisition and tracking (PAT) systems. The statistical misalignment model for detecting misalignment error is derived from the multiple transceivers. For the bi-directional characteristics of non-terrestrial back-haul networks, transmission performance is down-leveled to the worse in the asymmetric MIMO configuration of transceivers. The symmetric structure can mitigate the effect of increased pointing error to improve transmission performance. The proposed technique can be applied to the design of power-efficient FSO systems for non-terrestrial wireless back-haul networks.

Cooperative DF Protocol for MIMO Systems Using One-Bit ADCs.

This study considers a detection scheme for cooperative multi-input-multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs) in a decode-and-forward (DF) relay protocol. The use of one-bit ADCs is a promising technique for reducing the power consumption, which is necessary for supporting future wireless systems comprising a large number of antennas. However, the use of a large number of antennas remains still limited to mobile devices owing to their size. Cooperative communication using a DF relay can resolve this limitation; however, detection errors at the relay make it difficult to employ cooperative communication directly. This difficulty is more severe in a MIMO system using one-bit ADCs due to its nonlinear nature. To efficiently address the difficulty, this paper proposes a detection scheme that mitigates the error propagation effect. The upper bound of the pairwise error probability (PEP) of one-bit ADCs is first derived in a weighted Hamming distance form. Then, using the derived PEP, the proposed detection for the DF relay protocol is derived as a single weighted Hamming distance. Finally, the complexity of the proposed detection is analyzed in terms of real multiplications. The simulation results show that the proposed detection method efficiently mitigates the error propagation effect but has a relatively low level of complexity when compared to conventional detection methods.

Pan-cancer identification of the relationship of metabolism-related differentially expressed transcription regulation with non-differentially expressed target genes via a gated recurrent unit network.

The transcriptome describes the expression of all genes in a sample. Most studies have investigated the differential patterns or discrimination powers of transcript expression levels. In this study, we hypothesized that the quantitative correlations between the expression levels of transcription factors (TFs) and their regulated target genes (mRNAs) serve as a novel view of healthy status, and a disease sample exhibits a differential landscape (mqTrans) of transcription regulations compared with healthy status. We formulated quantitative transcription regulation relationships of metabolism-related genes as a multi-input multi-output regression model via a gated recurrent unit (GRU) network. The GRU model was trained using healthy blood transcriptomes and the expression levels of mRNAs were predicted by those of the TFs. The mqTrans feature of a gene was defined as the difference between its predicted and actual expression levels. A pan-cancer investigation of the differentially expressed mqTrans features was conducted between the early- and late-stage cancers in 26 cancer types of The Cancer Genome Atlas database. This study focused on the differentially expressed mqTrans features, that did not show differential expression in the actual expression levels. These genes could not be detected by conventional differential analysis. Such dark biomarkers are worthy of further wet-lab investigation. The experimental data also showed that the proposed mqTrans investigation improved the classification between early- and late-stage samples for some cancer types. Thus, the mqTrans features serve as a complementary view to transcriptomes, an OMIC type with mature high-throughput production technologies, and abundant public resources.

Multivariable advanced nonlinear controller for bioethanol production in a non-isothermal fermentation bioreactor.

Design for fermentation bioreactor controllers is challenged by the nonlinear process kinetics and the lack of online measurements for key variables. This work developed a multi-input, multi-output advanced nonlinear control structure for a continuous, non-isothermal, constant volume fermentation bioreactor. Utilizing feedback linearization control for the bioreactor feed to regulate glucose concentration, and backstepping control for the cooling jacket feed to regulate reactor temperature. A developed novel estimator for biomass concentration was incorporated to provide online estimates for the unmeasurable state variable. Simulation results showed the control structure ability in efficiently establishing a combination of dynamic and fixed set points, despite disturbances in the bioreactor feed temperature and glucose concentration. Expanded bioreactor control authority increased operational flexibility and enhanced the potential for performance improvements. This work illustrated the effectiveness of feedback linearization and backstepping control in designing controllers for biological systems with nonlinear dynamics, complex interactions, and input disturbances.

Medium-Sized Highly Coupled Planar Arrays with Maximum Aperture Efficiency.

This paper presents a technique to design strongly coupled planar arrays with very high aperture efficiency. The key innovation is that, based on an irregular 2 × 1 array, very compact medium-sized arrays of size 2 × 2, 2 × 4, and 2 × 6 are constructed with very strong and constructive mutual coupling between the elements. In this way, a maximum aperture efficiency is reached for a given footprint of the array. The occupied space of the antenna in comparison with conventional linear patch arrays is studied. A prototype 2 × 4 array operating around 5.8 GHz is designed, fabricated, built, and measured. The results show a large bandwidth of 20% and a very high aperture efficiency of 100%, which is the largest found in the literature for similarly sized arrays. These results are important in view of the future Internet of Things, where small and medium-sized arrays are planned to be mounted on numerous devices where a very limited physical area is available.

Broad Coverage Precoding for 3D Massive MIMO with Huge Uniform Planar Arrays.

In this paper, we propose a novel broad coverage precoder design for three-dimensional (3D) massive multi-input multi-output (MIMO) equipped with huge uniform planar arrays (UPAs). The desired two-dimensional (2D) angle power spectrum is assumed to be separable. We use the per-antenna constant power constraint and the semi-unitary constraint which are widely used in the literature. For normal broad coverage precoder design, the dimension of the optimization space is the product of the number of antennas at the base station (BS) and the number of transmit streams. With the proposed method, the design of the high-dimensional precoding matrices is reduced to that of a set of low-dimensional orthonormal vectors, and of a pair of low-dimensional vectors. The dimensions of the vectors in the set and the pair are the number of antennas per column and per row of the UPA, respectively. We then use optimization methods to generate the set of orthonormal vectors and the pair of vectors, respectively. Finally, simulation results show that the proposed broad coverage precoding matrices achieve nearly the same performance as the normal broad coverage precoder with much lower computational complexity.

Computationally Efficient Direction-of-Arrival Estimation Algorithms for a Cubic Coprime Array.

In this paper, we investigate the problem of direction-of-arrival (DOA) estimation for massive multi-input multi-output (MIMO) radar, and propose a total array-based multiple signals classification (TA-MUSIC) algorithm for two-dimensional direction-of-arrival (DOA) estimation with a coprime cubic array (CCA). Unlike the conventional multiple signal classification (MUSIC) algorithm, the TA-MUSIC algorithm employs not only the auto-covariance matrix but also the mutual covariance matrix by stacking the received signals of two sub cubic arrays so that full degrees of freedom (DOFs) can be utilized. We verified that the phase ambiguity problem can be eliminated by employing the coprime property. Moreover, to achieve lower complexity, we explored the estimation of signal parameters via the rotational invariance technique (ESPRIT)-based multiple signal classification (E-MUSIC) algorithm, which uses a successive scheme to be computationally efficient. The Cramer-Rao bound (CRB) was taken as a theoretical benchmark for the lower boundary of the unbiased estimate. Finally, numerical simulations were conducted in order to demonstrate the effectiveness and superiority of the proposed algorithms.

Design, implementation and model predictive based control of a mode-changeable DC/DC converter for hybrid renewable energy systems.

Since renewable energy sources such as PV and wind provide intermittent energy generation, this paper presents an advanced DC/DC converter that is able to set its operational mode automatically to either multi-input multi-output (MIMO) or single-input multi-output (SIMO) depending on the input source conditions. Power flow is controlled through the auxiliary relays added to a double-layer boost converter. Considering the transient events require fast dynamic response, model predictive control (MPC) is used to achieve the current control processes for both layers. Furthermore, the MPC is modified to adapt itself to changes in the topology. The proposed system is verified by simulations and experimentally. Results show that the proposed mode-changeable converter successfully determines the optimum power route after deciding the best operational mode in accordance with the input source conditions. Furthermore, the control method achieves a powerful and effective control process in both MIMO and SIMO modes.

A Novel MIMO-SAR System Based on Simultaneous Digital Beam Forming of Both Transceiver and Receiver.

Orthogonal frequency division multiplexing (OFDM) chirp waveform, which is composed of two or more successive identical linear frequency modulated sub pulses, is a newly proposed orthogonal waveform scheme for multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems. However, according to the waveform model, there will be range ambiguity if the mapping width exceeds the maximum unambiguous width determined by the transmitted signal. This greatly limits its application in high-resolution wide-swath (HRWS) remote sensing. The traditional system divides the echoes by digital beam forming (DBF) to solve this problem, but the energy utilization rate is low. A MIMO-SAR system using simultaneous digital beam forming of both transceiver and receiver to avoid range ambiguity is designed in this paper. Compared with traditional system, the novel system designed in this paper obtain higher energy utilization and waveform orthogonality.

Antenna Combining for Interference Limited MIMO Cellular Networks.

This paper considers a downlink cellular network where multi-antenna base stations (BSs) simultaneously serve their associated multi-antenna users. Each BS is distributed according to a homogeneous Poisson point process and uses zero-forcing beamforming for spatial division multiplexing with partial channel state information (CSI). During downlink transmission, each user combines the multiple antenna outputs and quantizes the CSI to feed back to its associated BS. Specifically, this paper focuses on antenna combining at the receiver. Conventional quantization-based combining (QBC) effectively reduces the quantization error; however, inter-cell interference in the cellular networks degrades the QBC gain. This degradation is analyzed using a spherical-cap approximation of vector quantization (SCVQ). From the SCVQ, the ergodic spectral efficiency and the optimal number of feedback bits are investigated, and it is shown that the QBC degrades the gain of the effective channel. To address this problem, an optimization solution is proposed that selects the antenna combining to maximize the spectral efficiency. The solution is also derived by considering the expected beamforming vectors of other cells. It is demonstrated by simulation that the proposed solution outperforms the conventional methods.

Adaptive approximation-based design mechanism for non-strict-feedback nonlinear MIMO systems with application to continuous stirred tank reactor.

This article is concerned with the problem of adaptive neural controller design for multi-input/multi-output nonlinear systems with input-saturations and disturbances. In the proposed design mechanism, we will take advantage of hyperbolic tangent functions to smooth the sharp corners of the input saturations and use Young's inequality to handle the nonlinear terms derived from the deducing process, and meanwhile apply the intelligent algorithm to estimate the unknown nonlinearity via neural networks. Furthermore, the backstepping technique is used to complete the design of the controller and Lyapunov stability theory is employed to show that the whole closed-loop system is semi-global uniformly ultimately bounded and the tracking error is bounded subject to the small neighborhood of the origin. Finally, as a practical application of the researched design scheme, adaptive neural controller for a continuous stirred tank reactor is constructed.

A Novel Orthogonal Waveform Separation Scheme for Airborne MIMO-SAR Systems.

In recent years, multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems, which can promote the performance of 3D imaging, high-resolution wide-swath remote sensing, and multi-baseline interferometry, have received considerable attention. Several papers on MIMO-SAR have been published, but the research of such systems is seriously limited. This is mainly because the superposed echoes of the multiple transmitted orthogonal waveforms cannot be separated perfectly. The imperfect separation will introduce ambiguous energy and degrade SAR images dramatically. In this paper, a novel orthogonal waveform separation scheme based on echo-compression is proposed for airborne MIMO-SAR systems. Specifically, apart from the simultaneous transmissions, the transmitters are required to radiate several times alone in a synthetic aperture to sense their private inner-aperture channels. Since the channel responses at the neighboring azimuth positions are relevant, the energy of the solely radiated orthogonal waveforms in the superposed echoes will be concentrated. To this end, the echoes of the multiple transmitted orthogonal waveforms can be separated by cancelling the peaks. In addition, the cleaned echoes, along with original superposed one, can be used to reconstruct the unambiguous echoes. The proposed scheme is validated by simulations.

A Novel Scheme for MIMO-SAR Systems Using Rotational Orbital Angular Momentum.

The vortex electromagnetic (EM) wave with orbital angular momentum (OAM) brings a new degree of freedom for synthetic aperture radar (SAR) imaging, although to date, its application to multi-input multi-output (MIMO) SAR has not yet been widely reported. In this paper, an orbital angular momentum (OAM)-based MIMO-SAR system is proposed. The rotational Doppler Effect (RDE) of vortex EM waves offers a novel scheme for an OAM-based MIMO-SAR system. By transmitting the rotational vortex EM waves, echoes of different OAM modes can be discriminated by a bandpass filter in the range-Doppler domain. The performance of the proposed scheme is independent of the time-variant channel responses, and the wider beam width of the vortex EM waves delivers, for the same antenna aperture size, better performance in terms of swath width and azimuth resolution, in contrast to the plane EM waves. Moreover, the spatial diversity of vortex EM waves shows great potential to enhance the MIMO-SAR system applications, which involve high-resolution wide-swath remote sensing, 3-D imaging, and radar-communication integration. The proposed scheme is verified by proof-of-concept experiments. This work presents a new application of vortex EM waves, which facilitates the development of new-generation and forthcoming SAR systems.

Data-driven model reference control of MIMO vertical tank systems with model-free VRFT and Q-Learning.

This paper proposes a combined Virtual Reference Feedback Tuning-Q-learning model-free control approach, which tunes nonlinear static state feedback controllers to achieve output model reference tracking in an optimal control framework. The novel iterative Batch Fitted Q-learning strategy uses two neural networks to represent the value function (critic) and the controller (actor), and it is referred to as a mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach. Learning convergence of the Q-learning schemes generally depends, among other settings, on the efficient exploration of the state-action space. Handcrafting test signals for efficient exploration is difficult even for input-output stable unknown processes. Virtual Reference Feedback Tuning can ensure an initial stabilizing controller to be learned from few input-output data and it can be next used to collect substantially more input-state data in a controlled mode, in a constrained environment, by compensating the process dynamics. This data is used to learn significantly superior nonlinear state feedback neural networks controllers for model reference tracking, using the proposed Batch Fitted Q-learning iterative tuning strategy, motivating the original combination of the two techniques. The mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach is experimentally validated for water level control of a multi input-multi output nonlinear constrained coupled two-tank system. Discussions on the observed control behavior are offered.

Modeling and control of non-square MIMO system using relay feedback.

This paper proposes a systematic approach for the modeling and control of non-square MIMO systems in time domain using relay feedback. Conventionally, modeling, selection of the control configuration and controller design of non-square MIMO systems are performed using input/output information of direct loop, while the output of undesired responses that bears valuable information on interaction among the loops are not considered. However, in this paper, the undesired response obtained from relay feedback test is also taken into consideration to extract the information about the interaction between the loops. The studies are performed on an Air Path Scheme of Turbocharged Diesel Engine (APSTDE) model, which is a typical non-square MIMO system, with input and output variables being 3 and 2 respectively. From the relay test response, the generalized analytical expressions are derived and these analytical expressions are used to estimate unknown system parameters and also to evaluate interaction measures. The interaction is analyzed by using Block Relative Gain (BRG) method. The model thus identified is later used to design appropriate controller to carry out closed loop studies. Closed loop simulation studies were performed for both servo and regulatory operations. Integral of Squared Error (ISE) performance criterion is employed to quantitatively evaluate performance of the proposed scheme. The usefulness of the proposed method is demonstrated on a lab-scale Two-Tank Cylindrical Interacting System (TTCIS), which is configured as a non-square system.