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Fundamentals of MIMO wireless communications
\"Provides a solid understanding of the essential concepts of MIMO wireless communications\"-- Provided by publisher.
Book
A Review of Industrial MIMO Decoupling Control
In recent decades, MIMO (Multi-Input-Multi-Output) systems become more and more widely used in industrial applications. A variety of decoupling control algorithms have been studied in the literature. Therefore, a review of the most extensively applied coupling interaction analysis and decoupler design methods for industrial processes is necessary to be carried out. In this paper, in order to benefit researchers and engineers with different academic backgrounds, the scattered coupling interaction analysis and decoupling algorithms are collected and divided into different categories with their characteristics, application domains and informative comments for selection. Moveover, some frequently concerned problems of decoupling control are also discussed.
Journal Article
Structured compressive sensing based superimposed pilot design in downlink large-scale MIMO systems
Large-scale multiple-input multiple-output (MIMO) with high spectrum and energy efficiency is a very promising key technology for future 5G wireless communications. For large-scale MIMO systems, accurate channel state information (CSI) acquisition is a challenging problem, especially when each user has to distinguish and estimate numerous channels coming from a large number of transmit antennas in the downlink. Unlike the conventional orthogonal pilots whose pilot overhead prohibitively increases with the number of transmit antennas, a spectrum-efficient superimposed pilot design for downlink large-scale MIMO scenarios is proposed, where frequency-domain pilots of different transmit antennas occupy completely the same subcarriers in the frequency domain. Meanwhile, spatial–temporal common sparsity of large-scale MIMO channels motivates us to exploit the emerging theory of structured compressive sensing (CS) for reliable MIMO channel estimation, which is realised by the proposed structured subspace pursuit (SSP) algorithm to simultaneously recover multiple channels with low pilot overhead. Simulation results demonstrate that the proposed scheme performs well and can approach the performance bound.
Journal Article
Physical layer security schemes for MIMO systems: an overview
Physical layer security (PLS) has become an increasingly attractive topic since it promises current and future wireless systems both reliable and secure communication, without imposing any assumptions on the computational power of the eavesdroppers. PLS benefits from the randomness property of the wireless channel, which provides better immunity and prevents different attacks. On the other hand, the multiple-input multiple-output (MIMO) system has emerged as a key technology to support high data rates and improved energy and spectral efficiency, in addition to overcoming the effect of shadowing and fading. Recently, MIMO-based PLS has been addressed in the literature due to its wide adoption and its essential role in wireless communication systems. In this paper, we provide a comprehensive overview of various MIMO-based PLS techniques that target all kinds of security services namely, key generation and distribution, data confidentiality, authentication, and availability. With this overview, readers will have a better understanding of the MIMO-based PLS techniques present in the literature, their current limitations, and challenges.
Journal Article
Spectral Efficiency Analysis for Massive MIMO System Under QoS Constraint: an Effective Capacity Perspective
In massive multiple-input multiple-output (MIMO) systems, dozens of mobile users can simultaneously receive signals from one base station. To obtain maximum spectral efficiency (SE), researchers have investigated the optimal number of scheduled users for one time slot. However, in practical cases, we must consider the quality of service (QoS) constraint. The probability of delay violation is an important QoS index that depends on transmission stability over a long period rather than the instantaneous transmission rate of one time slot. In this paper, we analyze the achievable effective SE of a massive MIMO system under the probability constraint of delay violation. By adopting the effective capacity (EC) theory of wireless channels, we associate the delay violation probability with the transmission rate fluctuations caused by the massive MIMO scheduling strategy used. The relationship between the effective SE, the QoS constraint, and the number of scheduled users is formulated as a continuous function. Our simulation results demonstrate how the optimal number of scheduled users changes for different QoS constraint levels. According to the changing trend, the massive MIMO system can be programmed to choose between different simple scheduling strategies for different QoS constraint levels.
Journal Article
Optimal Model Approximation of Linear Time-Invariant Systems Using the Enhanced DE Algorithm and Improved MPPA Method
In this paper, the authors propose a novel model order reduction method integrating evolutionary and conventional approaches for higher-order linear time-invariant single-input–single-output (SISO) and multi-input–multi-output (MIMO) dynamic systems. The proposed method makes use of a differential evolution algorithm with enhanced mutation operation for the determination of reduced order model (ROM) denominator polynomial coefficients. In addition, an improved multi-point Padé approximation method is used to determine the optimal ROM numerator polynomial coefficients. The optimum property of the ROM is measured by minimising the integral square of the step response error between the original high-order dynamic system and the ROM. In the case of the MIMO system reduction approach, an optimal ROM transfer function matrix is determined by minimising a single objective function. This objective function is defined by a linear scalarising of the multi-step error function matrix components Eij. The proposed method guarantees the preservation of the stability, passivity and accuracy of the original higher-order system in the ROM. The proposed method is validated by applying it to a ninth-order SISO system, as well as to the tenth- and sixth-order linearised single-machine infinite-bus power system model with and without an automatic excitation control system. The simulation results and the comparison of the integral square error and impulse response energy values of the ROM demonstrate the dominance of the proposed method over the latest reduction methods available in the literature.
Journal Article
A new harmonic probing algorithm for computing the MIMO Volterra frequency response functions of nonlinear systems
Frequency domain Volterra analysis of MIMO nonlinear systems is complicated by the need to keep track not only of the multi-dimensional interactions between frequencies, but also of the inputs at which these frequencies are applied and the outputs at which the response is observed. A new notation has been introduced which helps clarify this analysis, simplifying issues of kernel symmetry and opening a pathway for more general proofs and automated computation. The new notation is then used to prove and develop a new MIMO harmonic probing algorithm which allows simultaneous probing on multiple inputs, in contrast to prior work which requires sequentially setting other inputs to zero in order to isolate the response of each MIMO frequency response function (FRF) in turn. The method is illustrated through the analysis of a coupled nonlinear mass-spring-damper system and provides new insight into the structure of the FRFs in this case.
Journal Article
A joint resource allocation method for multiple targets tracking in distributed MIMO radar systems
In order to simultaneously improve system performance and resource utilization of distributed multiple-input multiple-output (MIMO) radar systems, a joint resource allocation method is proposed to address the velocity estimation problem for multiple targets tracking in this paper. The paper focuses to improve the tracking performance for key targets using the remaining resources when the general targets have obtained resources to reach to tracking requirements. Firstly, a criterion minimizing the velocity estimation mean square error (MSE) for a key target is considered. Restricted by limited and relatively sufficient system resources and given velocity estimation requirements for general targets, a joint resource allocation optimization model with transmitters, receivers, transmitted power, and signal time is established. We propose a suboptimal method to approximately solve this problem. The method separates the optimization into three steps, where each step transforms the corresponding mixed-Boolean optimization problem into a second-order cone programming (SOCP) problem by convex relaxation. Finally, the approximately optimal solution can be obtained by cyclic minimization method. Extensive simulations indicate that compared with other methods, the proposed joint method can achieve the lowest velocity estimation MSE with the fewest transmitters. Meanwhile, limited by the given velocity estimation MSE, the proposed method can focus on the key target and achieve the whole velocity estimation error minimization while a greater flexibility for target tracking number can be obtained. Moreover, random experiments can further validate and evaluate the proposed method’s effectiveness and traceability with the given scenario.
Journal Article
Adaptive neural inverse optimal control with predetermined tracking accuracy for nonlinear MIMO systems
In addition to stability, the system optimality has also received attention because the system is expected to achieve higher performance with lower energy consumption. In general, the conventional approach to achieve optimal control of nonlinear MIMO systems is to solve the Hamilton–Jacobi–Bellman equation directly, which is time-consuming and sometimes impossible. To address this issue, this paper proposes an adaptive neural inverse optimal control method for uncertain MIMO systems. The method is based on an improved design criterion for the inverse optimal controller, which avoids the need for constructing auxiliary systems and enables direct stability analysis of MIMO systems. Additionally, an adaptive one-parameter update strategy is proposed to reduce the computational effort, which avoids the need to update the entire neural network. The proposed scheme guarantees that the tracking errors of the MIMO system converge to a given domain while minimizing a family of meaningful loss functions. Finally, the effectiveness of the presented method is verified through simulations.
Journal Article
A combining design of precoder and equalizer based on shared redundancy to improve performance of ISI MIMO systems
There have been a number of researches on block transmission systems via MIMO channels due to really high data transmission rate. However, because of the existence of inter-symbol interference (ISI) in the systems, guard intervals are added to eliminate the ISI, leading to a reduction in channel energy and bandwidth efficiency. In order to optimize these systems, there are many solutions in which a combining design of precoder and equalizer appears as a potential candidate. In this paper, a jointly optimal design for precoder and equalizer for ISI multiple input multiple output (MIMO) channels based on sharing redundancy is proposed. Theory analysis and simulation results demonstrate that the proposed design produces a significant improvement in the system performance such as a reduction in bit error rate, a decrease in channel energy loss and an increase in system throughput.
Journal Article