Passive Beamforming Design for Intelligent Reflecting Surface Assisted MIMO Systems

Intelligent reflecting surfaces(IRSs)constitute passive devices,which are capable of adjusting the phase shifts of their reflected signals,and hence they are suitable for passive beamforming.In this paper,we conceive their design with the active beamforming action of multiple-input multipleoutput(MIMO)systems used at the access points(APs)for improving the beamforming gain,where both the APs and users are equipped with multiple antennas.Firstly,we decouple the optimization problem and design the active beamforming for a given IRS configuration.Then we transform the optimization problem of the IRS-based passive beamforming design into a tractable non-convex quadratically constrained quadratic program(QCQP).For solving the transformed problem,we give an approximate solution based on the technique of widely used semidefinite relaxation(SDR).We also propose a low-complexity iterative solution.We further prove that it can converge to a locally optimal value.Finally,considering the practical scenario of discrete phase shifts at the IRS,we give the quantization design for IRS elements on basis of the two solutions.Our simulation results demonstrate the superiority of the proposed solutions over the relevant benchmarks.

A Survey on Channel Measurements and Models for Underground MIMO Communication Systems

The high reliability of the communication system is critical in metro and mining applications for personal safety,channel optimization,and improving operational performance.This paper surveys the progress of wireless communication systems in underground environments such as tunnels and mines from 1920 to 2022,including the evolution of primitive technology,advancements in channel modelling,and realization of various wireless propagation channels.In addition,the existing and advanced channel modeling strategies,which include the evolution of different technologies and their applications;mathematical,analytical,and experimental techniques for radio propagation;and significance of the radiation characteristics,antenna placement,and physical environment of multiple-input multiple-output(MIMO)communication systems,are analyzed.The given study introduces leaky coaxial cable(LCX)and distributed antenna system(DAS)designs for improving narrowband and wideband channel capacity.The paper concludes by figuring out open research areas for the future technologies.

Performance Evaluation of a Four-Element Antenna Array with Selection Circuits for Adaptive MIMO Systems

Reconfigurable antenna arrays increase the flexibility of adaptive MIMO systems. At present, most designs have adopted antenna arrays with reconfigurable elements. However, antenna selection is also an effective method, which has not been fully investigated. In this paper, the potential benefits of a four-element antenna array with selection circuits in the UMTS band （1920-2170 MHz） are explored. The array has eight pin-diodes embedded in the feeding network to select any sub-set of elements. For evaluation, an adaptive MIMO system was set up and a measurement campaign was taken in an indoor multi-path environment. The measurements were performed over a 300 MHz bandwidth centered at 2.05 GHz, covering the UMTS band. The results show that different channel conditions prefer different antenna array configurations. Therefore, in varying channel conditions the antenna array can support antenna selection algorithms to select the best sub-set of elements to increase channel capacity.

Angle estimation for bistatic MIMO radar with unknown mutual coupling based on three-way compressive sensing

The problem of angle estimation for bistatic multiple-input multiple-output radar in the present of unknown mutual coupling (MC) is investigated, and a three-way compressive sensing (TWCS) estimation algorithm is developed. To exploit the inherent multi-dimensional structure of received data, a trilinear tensor model is firstly formulated. Then the de-coupling operation is followed. Thereafter, the high-order singular value decomposition is applied to compress the high dimensional tensor to a much smaller one. The estimation of the compressed direction matrices are linked to the compressed trilinear model, and finally two over-complete dictionaries are constructed for angle estimation. Also, Cramer-Rao bounds for angle and MC estimation are derived. The proposed TWCS algorithm is effective from the perspective of estimation accuracy as well as the computational complexity, and it can achieve automatically paired angle estimation. Simulation results show that the proposed method has much better estimation accuracy than the existing algorithms in the low signal-to-noise ratio scenario, and its estimation performance is very close to the parallel factor analysis (PARAFAC) algorithm at the high SNR regions. © 2017 Beijing Institute of Aerospace Information.

On the MIMO channel capacity saturation for spatially constrained receive region

In MIMO wireless communication systems, when more and more antennas are packed into spatiallylimited receive region, the antenna saturation phenomenon will appear. Moreover, the electromagnetic interactions among antennas will also become stronger and stronger and affect the antenna saturation effect considerably. Despite this, few studies consider these two effects jointly. The effects of antenna saturation are investigated under the consideration of mutual coupling, thus a more practical and physically meaningful result can be obtained.

Adaptive control of linear multivariable systems with high frequency gain matrix hurwitz

A new adaptive control scheme is proposed for multivariable model reference adaptive control （MRAC） systems based on the nonlinear backstepplng approach with vector form. The assumption on a priori knowledge of the high frequency gain matrix in existing results is relaxed and the new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. This control scheme guarantees the global stability of the closed-loop systems and the tracking error can be arbitrary small. The simulation result for an application example shows the validity of the proposed nonlinear adaptive scheme.

Output feedback adaptive control of multivariable nonlinear systems using Nussbaum gain method

A new output feedback adaptive control scheme for multi-input and multi-output nonlinear systems with parametric uncertainty is presented based on the Nussbaum gain method and the backstepping approach. The high frequency gain matrix of the linear part of the system is not necessarily positive definite, but can be transformed into a lower or upper triangular matrix whose signs of diagonal dements are unknown. The new required condition for the high fi＇equency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. The global stability of the closed loop systems is guaranteed through this control scheme, at the same time the tracking error converges to zero.

Component fault diagnosis for nonlinear systems

In the field of fault diagnosis, the state equation of nonlinear system, including the actuator and the component, has been established. When the faults in the system appear, it is difficult to observe the fault isolation between the actuator and the component. In order to diagnose the component fault in the nonlinear systems, a novel strategy is proposed. The nonlinear state equation with only the component system is built on mathematical equations. The nonlinearity of the component equation is expanded and estimated with Taylor series. If the actuator is perfect, the anomaly of the state equations reflects the component fault. The fault feature index is defined to detect the component fault and the initial fault. The numerical examples of the component faults are simulated for multiple-input multiple-output(MIMO)nonlinear systems. The results show that the component faults,as well as the incipient faults, can be detected. Furthermore, the effectiveness of the proposed strategy is verified. This method can also provide a foundation for the component fault reconfiguration control.

Adaptive Tracking Control for Output-Constrained Switched MIMO Pure-Feedback Nonlinear Systems with Input Saturation

In this paper,an adaptive neural tracking control scheme for a class of uncertain switched multi-input multi-output(MIMO)pure-feedback nonlinear systems is proposed.The considered MIMO pure-feedback nonlinear system contains input and output constraints,completely unknown nonlinear functions and time-varying external disturbances.The unknown nonlinear functions representing system uncertainties are identified via radial basis function neural networks(RBFNNs).Then,the Nussbaum function is utilized to deal with the nonlinearity issue caused by the input saturation.To prevent system outputs from violating prescribed constraints,the barrier Lyapunov functions(BLFs)are introduced.Also,a switched disturbance observer is designed to make the time-varying external disturbances estimable.Based on the backstepping recursive design technique and the Lyapunov stability theory,the developed control method is verified applicable to ensure the boundedness of all signals in the closed-loop system and make the system output track given reference signals well.Finally,a numerical simulation is given to demonstrate the effectiveness of the proposed control method.

Reduced K-best sphere decoding algorithm based on minimum route distance and noise variance

This paper focuses on reducing the complexity of K-best sphere decoding （SD） algorithm for the detection of uncoded multi-ple input multiple output （MIMO） systems. The proposed algorithm utilizes the threshold-pruning method to cut nodes with partial Euclidean distances （PEDs） larger than the threshold. Both the known noise value and the unknown noise value are considered to generate the threshold, which is the sum of the two values. The known noise value is the smal est PED of signals in the detected layers. The unknown noise value is generated by the noise power, the quality of service （QoS） and the signal-to-noise ratio （SNR） bound. Simulation results show that by considering both two noise values, the proposed algorithm makes an efficient reduction while the performance drops little.

Output Feedback Stabilization for MIMO Semi-linear Stochastic Systems with Transient Optimisation

This paper investigates the stabilisation problem and consider transient optimisation for a class of the multi-input-multi-output(MIMO)semi-linear stochastic systems.A control algorithm is presented via an m-block backstepping controller design where the closed-loop system has been stabilized in a probabilistic sense and the transient performance is optimisable by optimised by searching the design parameters under the given criterion.In particular,the transient randomness and the probabilistic decoupling will be investigated as case studies.Note that the presented control algorithm can be potentially extended as a framework based on the various performance criteria.To evaluate the effectiveness of this proposed control framework,a numerical example is given with simulation results.In summary,the key contributions of this paper are stated as follows:1)one block backstepping-based output feedback control design is developed to stabilize the dynamic MIMO semi-linear stochastic systems using a linear estimator;2)the randomness and probabilistic couplings of the system outputs have been minimized based on the optimisation of the design parameters of the controller;3)a control framework with transient performance enhancement of multi-variable semi-linear stochastic systems has been discussed.

The Learning Control and Learning Adaptive Control of General Nonlinear Systems：MIMO Case

The learning control law for the general MIMO nonlinear systems with white noise distrubance is presented in the paper,it has extremely simple, recursive, incremental form,and strong robustness,it can also deal with the ill-conditioned systems.The new adaptive control scheme is presented when the parameters of the MIMO nonlinear systems are unknown.The convergence,BIBO stability,and robustness of learning adaptive control scheme are also discussed in this paper.

Design of Non-rational MIMO Feedback Systems with Inputs and Outputs Satisfying Certain Bounding Conditions by Using Rational Approximants

When a feedback system has components described by non-rational transfer functions, a standard practice in designing such a system is to replace the non-rational functions with rational approximants and then carry out the design with the approximants by means of a method that copes with rational systems. In order to ensure that the design carried out with the approximants still provides satisfactory results for the original system, a criterion of approximation should be explicitly taken into account in the design formulation. This paper derives such a criterion for multi-input multi-output（MIMO） feedback systems whose design objective is to ensure that the absolute values of every error and every controller output components always stay within prescribed bounds whenever the inputs satisfy certain bounding conditions. The obtained criterion generalizes a known result which was derived for single-input single-output（SISO） systems; furthermore, for a given rational approximant matrix, it is expressed as a set of inequalities that can be solved in practice. Finally, a controller for a binary distillation column is designed by using the criterion in conjunction with the method of inequalities. The numerical results clearly demonstrate that the usefulness of the criterion in obtaining a design solution for the original system.

EXIT analysis of M-algorithm based MIMO detectors and LDPC code design optimization

This paper investigates joint design and optimization of both low density parity check （LDPC） codes and M-algorithm based detectors including iterative tree search （ITS） and soft-output M-algorithm （SOMA） in multiple-input multiple-output （MIMO） systems via the tool of extrinsic information transfer （EXIT） charts. First, we present EXIT analysis for ITS and SOMA. We indicate that the extrinsic information transfer curves of ITS obtained by Monte Carlo simulations based on output log-likelihood rations are not true EXIT curves, and the explanation for such a phenomenon is given, while for SOMA, the true EXIT curves can be computed, enabling the code design. Then, we propose a new design rule and method for LDPC code degree profile optimization in MIMO systems. The algorithm can make the EXIT curves of the inner decoder and outer decoder match each other properly, and can easily attain the desired code with the target rate. Also, it can transform the optimization problem into a linear one, which is computationally simple. The significance of the proposed optimization approach is validated by the simulation results that the optimized codes perform much better than standard non-optimized ones when used together with SOMA detector.

Multiuser beamforming based on max SINR for downlink spatial multiplexing MIMO

In this article, a method based on max signal interference noise ratio（SINR） criterion is proposed, to mitigate the interuser interference for downlink multiuser spatial multiplexing multi-input multi-output（MIMO） systems. Unlike the zero forcing （ZF） scheme in which the SNR is decreased when the interference is eliminated completely, max SINR method makes a compromise between noise and interuser interference. When the number of substreams is larger than the difference between the number of base station antennas and the sum of interference mobile station antennas, the ZF is infeasible An existing coordinated TX-RX block diagonalization（COOR BD） method uses preprocessing at the receiver to cancel the interuser interference. However, it cannot obtain more receive diversity gain because of the preprocessing. Analysis and simulation show that the max SINR scheme has better performance than the ZF method. Moreover, when the ZF is infeasible, the max SINR scheme can obtain more receive diversity gain than COOR BD in the two-user case.

Sub-channel interference cancellation in SVD-based MIMO system

For singular value decomposition （SVD）-based multiple input multiple output （MIMO） systems, implicit channel state information （CSI） incurs interferences amongst sub-channels if the CSI at the transmitter is not explicit. An improved SVD-based MIMO which can fully cancel the inter sub-channel interferences by reconstructing the transmitter- receiver system matrix on interferences analysis is provided. Simulation results indicate that the proposed algorithm outperforms the traditional SVD-based MIMO in a large degree.

Channel Capacity Estimation in TDMS-Based MIMO Measurements

Time-division multiplexed switching （TDMS）-based multiple-input multiple-output （MIMO） channel sounders are widely used for wireless channel measurements due to their effective costs. However, meas- urement noise such as phase noise in the local oscillators as well as additive white Gaussian noise （AWGN） can result in significant errors in channel capacity estimates. This study analyzes the impact of phase noise and AWGN on channel capacity in TDMS-based MIMO measurements, with a channel capacity estimator presented that reduces the impact of noise on both the spatial multiplexing gain and on the power gain. Simulations demonstrate that the estimator consistently obtains the true capacity for various MIMO channel scenarios, even if only a limited number of observations are available.

Energy-efficiency based downlink multi-user hybrid beamforming for millimeter wave massive MIMO system

The fifth generation mobile communication（5G） systems can provide Gbit/s data rates from massive multiple-input multiple-output（MIMO） combined with the emerging use of millimeter wavelengths in small heterogeneous cells. This paper develops an energy-efficiency based multi-user hybrid beamforming for downlink millimeter wave（mm Wave） massive MIMO systems. To make better use of directivity gains of the analog beamforming and flexible baseband processing of the digital beamforming, this paper proposes the analog beamforming to select the optimal beam which can maximize the power of the objective user and minimize the interference to all other users. In addition, the digital beamforming maximizes the energy efficiency of the objective user with zero-gradient-based approach. Simulation results show the proposed algorithm provide better bit error rate（BER） performance compared with the traditional hybrid beamforming and obviously improved the sum rate with the increase in the number of users. It is proved that multi-user MIMO（MU-MIMO） can be a perfect candidate for mm Wave massive MIMO communication system. Furthermore, the analog beamforming can mitigate the inter-user interference more effectively with the selection of the optimal beam and the digital beamforming can greatly improve the system performance through flexible baseband processing.

Artificial neural network approach for analyzing mutual coupling in a rectangular MIMO antenna

A wideband rectangular patch antenna resonat- ing at 3.5 GHz and 8 GHz frequencies is developed on a flexible substrate, which can be used for wearable applications. The proposed antenna gives a wide impe- dance bandwidth of 116%, operating from 2.SGHz to 9.5 GHz, covering most of the ultra-wideband （UWB） operating frequency range. A two-element multiple-input multiple-output （MIMO） system is developed using the proposed antenna, and the mutual coupling between the two antennas for various separations and frequencies is analyzed by using artificial neural networks （ANNs）. The neural structure is trained by using different ANN algorithms and a comparative study is made between them. It is shown that, quasi-Newton （QN） and quasi- Newton multi layer perceptron （QN-MLP） algorithms are better in terms of training, testing errors, and correlation coefficient.

Differential space-time block-diagonal codes

A new differential space-time code, called differential space-time block-diagonal code （DSTBDC）, is proposed for multiple-input multiple-output （MIMO） wireless communication systems. By exploiting the block-diagonal construction of DSTBDC, we can design a variety of high-performance DSTBDC, especially for the cases of large numbers of transmit antennas and high date rates. In flat fading channels, DSTBDC outperforms traditional differential space-time codes if the data rate is higher than 1 bps/Hz, especially when the number of transmit antennas is large. In frequency-selective fading channels, multiple-input multiple-output orthogonal frequency-division multiplexing （MIMO-OFDM） systems using DSTBDC have the powerful ability to achieve very high diversity gain in space, time, and frequency simultaneously. Due to the special orthogonal construction, DSTBDC has a simple decoding algorithm. In addition, DSTBDC can significantly save the cost of radio frequency circuits.