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 HOS-based Blind Signal Extraction Method for Chaotic MIMO Systems

A novel method to extract multiple input and multiple output (MIMO) chaotic signals was proposed using the blind neural algorithm after transmitting in nonideal channel. The MIMO scheme with different chaotic signal generators was presented. In order to separate the chaotic source signals only by using the sensor signals at receivers, a blind neural extraction algorithm based on higher-order statistic (HOS) technique was used to recover the primary chaotic signals. Simulation results show that the proposed approach has good performance in separating the primary chaotic signals even under nonideal channel.

Antenna selection based on large-scale fading for distributed MIMO systems

An antenna selection algorithm based on large-scale fading between the transmitter and receiver is proposed for the uplink receive antenna selection in distributed multiple-input multiple-output(D-MIMO) systems. By utilizing the radio access units(RAU) selection based on large-scale fading,the proposed algorithm decreases enormously the computational complexity. Based on the characteristics of distributed systems,an improved particle swarm optimization(PSO) has been proposed for the antenna selection after the RAU selection. In order to apply the improved PSO algorithm better in antenna selection,a general form of channel capacity was transformed into a binary expression by analyzing the formula of channel capacity. The proposed algorithm can make full use of the advantages of D-MIMO systems,and achieve near-optimal performance in terms of channel capacity with low computational complexity.

Iteration-stopping scheme of turbo receiver in turbo-MIMO systems

The iteration-stopping scheme of turbo receiver, consisting of an inner multiple-input multiple-output （MIMO） detector and an outer turbo decoder, was studied in this paper. In the inner MIMO detector, only the reliabilities of bits in those channel slots which included unreliable information bits were updated when the outer turbo code was a systematical one. In conjunction with the trigger events for stopping the turbo decoding, an iteration-stopping scheme of turbo receiver was proposed. Simulation results show that the proposed scheme has lower complexity, but almost the same error performance compared to the scheme with predetermined maximum iterations.

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.

Adaptive Control of MIMO Mechanical Systems with Unknown Actuator Nonlinearities Based on the Nussbaum Gain Approach

This paper investigates MIMO mechanical systems with unknown actuator nonlinearities. A novel Nussbaum analysis tool for MIMO systems is established such that unknown time-varying control coefficients are tackled. In contrast to existing literatures on continuous-time systems, the newly-developed Nussbaum tool focuses on extending the traditional Nussbaum result from one dimensional case to the multiple one. Specifically, not only the multiple unknown input coefficients are extended to the time-varying, but also the limitation of the prior knowledge of coefficients' upper and lower bounds is removed. Furthermore, an adaptive robust controller associated with the proposed tool is presented. The asymptotic tracking of MIMO mechanical systems is guaranteed with the help of the Lyapunov Theorem. Finally, a simulation example is provided to examine the validity of the proposed scheme. © 2014 Chinese Association of Automation.

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.

Improved iterative breadth-first detection algorithms for MIMO wireless systems

A reduced-complexity detection algorithm is proposed, which is applied to iterative receivers for multiple-input multiple-output （MIMO） systems. Unlike the exhaustive search over all the possible trans-mitted symbol vectors of the optimum maximum a posteriori probability （MAP） detector, the new algo-rithm evaluates only the symbol vectors that contribute significantly to the soft output of the detector. The algorithm is facilitated by carrying out the breadth-first search on a reconfigurable tree, constructed by computing the symbol reliability of each layer based on zero-forcing criterion and reordering the symbols according to the symbol reliabilities. Simulations are presented and the good performance of the new algo-rithm over a quasi-static Rayleigh channel even for relatively small list sizes are proved.

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.

Design and implementation of space-time precoded systems with full diversity and lossless capacity

A new space-time(ST)code design is proposed based on the design criteria of space-time codes,which is applied to the MIMO systems with fewer receive antennas than transmit antennas.The space-time codes,referred to as full diversity lossless capacity(FDLLC)ST code,achieve full transmit diversity and lossless equivalent channel capacity for ST precoded systems.Combined FDLLC-ST codes with channel codes,ST bit interleaved coded modulation(ST-BICM)system is constructed and an iterative detector/decoder is employed at the receiver.Simulations are presented.It is proved that the proposed design has good performance compared with other ST precoded MIMO systems.

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.

Robust MSE precoder for imperfectly known MIMO wireless correlated channel

Aimed at that only one form of channel statistic information is utilized in traditional robust precoder schemes: either the channel mean or the transmit antenna correlation in multiple-input multiple-output (MIMO) wireless system, this paper proposes robust precoder designs which exploit both of statistic information to minimize the equalization mean-square error (MSE) with power constraint. Two different power constraints are studied. Besides the usual sum power constraint over all antennas, the per-antenna power constraint is imposed at transmitter in this paper. Since each antenna has its own amplifier, individual power constraint on each antenna is more realistic. Especially in MIMO-OFDM systems, the Peak-to-Average Ratio (PAR) is one of main practical problems. Simulations show that the proposed schemes have better performance than traditional normalized zero forcing schemes for imperfectly known correlated channel. Moreover, per-antenna power constraint can efficiently decrease the demand of dynamic range of power amplifier on each transmit antenna, especially in MIMO-OFDM systems.

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.

Decoupling Trajectory Tracking for Gliding Reentry Vehicles

A decoupling trajectory tracking method for gliding reentry vehicles is presented to improve the reliability of the guidance system. Function relations between state variables and control variables are analyzed. To reduce the coupling between control channels, the multiple-input multiple-output (MIMO) tracking system is separated into a series of two single-input single-output (SISO) subsystems. Tracking laws for both velocity and altitude are designed based on the sliding mode control (SMC). The decoupling approach is verified by the Monte Carlo simulations, and compared with the linear quadratic regulator (LQR) approach in some specific conditions. Simulation results indicate that the decoupling approach owns a fast convergence speed and a strong anti-interference ability in the trajectory tracking. © 2014 Chinese Association of Automation.

A Concise Joint Transmit/Receive Antenna Selection Algorithm

For reducing the computational complexity of the problem of joint transmit and receive antenna selection in Multiple-Input-Multiple-Output (MIMO) systems, we present a concise joint transmit/receive antenna selection algorithm. Using a novel partition of the channel matrix, we drive a concise formula. This formula enables us to augment the channel matrix in such a way that the computational complexity of the greedy Joint Transmit/Receive Antenna Selection (JTRAS) algorithm is reduced by a factor of 4n L , where n L is the number of selected antennas. A decoupled version of the proposed algorithm is also proposed to further improve the efficiency of the JTRAS algorithm, with some capacity degradation as a tradeoff. The computational complexity and the performance of the proposed approaches are evaluated mathematically and verified by computer simulations. The results have shown that the proposed joint antenna selection algorithm maintains the capacity perormance of the JTRAS algorithm while its computational complexity is only 1/4n L of that of the JTRAS algorithm. The decoupled version of the proposed algorithm further reduces the computational complexity of the joint antenna selection and has better performance than other decoupling-based algorithms when the selected antenna subset is small as compared to the total number of antennas.

Capacity and QoS Based Codebook Construction for MIMO Precoded Spatial Multiplexing Systems with Limited Feedback

This paper deals with the design and performance analysis of transmit precoder optimization for multiple input multiple output(MIMO) systems with limited feedback of channel state information.A capacity criterion based optimal codebook construction algorithm for MIMO precoded spatial multiplexing systems is presented. The optimal precoder structure combining precoding and power allocation is employed.Simulation results show that the capacity criteria based codebook can achieve higher capacity than that of equally power allocation based codebook of previous research.

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.