Multiple-input And Multiple-output Systems Research Articles

Simulation of MIMO channel characteristics for indoor visible light communication with LEDs

In order to study the characteristics of multiple input and multiple output (MIMO) channel, first, the basic components of the communication system are analyzed. And then, we present a simplified ray tracing method for optical MIMO system to obtain its channel impulse response and frequency response. This method using ray tracing to calculate the impulse of the channel limits the reflections within three times. Finally, its validity is verified by the numerical simulations, and its simulation results have been discussed. The channel bandwidth is gradually narrow, direct response is getting small, and the first response becomes large from the center to the corner.

Water-Filling Solution for Distributed Estimation of Correlated Data in WSN MIMO System

We consider the distributed estimation of a random vector signal in a power constraint wireless sensor network (WSN) that follows a multiple-input and multiple-output (MIMO) coherent multiple access channel model. We design linear coding matrices based on linear minimum mean-square error (LMMSE) fusion rule that accommodates spatial correlated data. We obtain a closed-form solution that follows a water-filling strategy. We also derive a lower bound to this model. Simulation results show that when the data is more correlated, the distortion in terms of mean-square error (MSE) degrades. By taking into account the effects of correlation, observation, and channel matrices, the proposed method performs better than equal power method.

The Extraction of Simple Relationships in Growth Factor-Specific Multiple-Input and Multiple-Output Systems in Cell-Fate Decisions by Backward Elimination PLS Regression

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

Channel Characterisation and Link Budget of MIMO Configuration in Near Field Magnetic Communication

Abstract Traditional radio communication has gained significantly from using multiple input and multiple output (MIMO) architecture in the system. Many wireless applications, such as wireless LAN and cellular network, have adopted this technology to improve their system performance. However, the effect of MIMO systems has not been investigated in the case of inductive near field short range communications. The purpose of this paper is to explore a new method for increasing the magnetic communication range using MIMO. Three system models includingMISO, SIMO and MIMO are proposed to characterize the number of transmitters and receivers to the link. These models have helped to extend not only the range but also the communication channel in NFMIC.

Hybrid system identification for high-performance structural control

Structural systems installed with active or semi-active control devices usually require availability of a high-fidelity model to determine appropriate control designs. Use of traditional system identification techniques has proven to be challenging, primarily due to the fact that such models must be multiple-input and multiple-output (MIMO) systems; the inputs correspond to the excitation and the control commands, while the outputs correspond to the measured responses. Even if a model is identified that can represent well the response of the structure, this model is often a non-minimal realization (i.e., the dynamics of various modes are duplicated in the model); these extra dynamics can degrade the performance of the resulting controller. This paper presents a hybrid system identification approach that can result in minimal (or near-minimal) realizations of the MIMO structure–control system models that are effective for structural control design. The first step in this approach develops a simplified model which can portray adequately the system characteristics found in the experimental data. Using information about the pole–zero relationship of the transfer function in the simplified model, a frequency-domain system identification strategy is employed subsequently to derive multiple single-input and multiple-output (SIMO) models with respect to each system input. The systems are then combined to determine the complete MIMO system model that is accurate over the frequency range of interest for the control applications. To demonstrate this hybrid approach, an example is provided to illustrate a high-fidelity identification result from the experiment of an actively isolated building system. Successful control implementation demonstrates the efficacy of this hybrid system identification approach.Structural systems installed with active or semi-active control devices usually require availability of a high-fidelity model to determine appropriate control designs. Use of traditional system identification techniques has proven to be challenging, primarily due to the fact that such models must be multiple-input and multiple-output (MIMO) systems; the inputs correspond to the excitation and the control commands, while the outputs correspond to the measured responses. Even if a model is identified that can represent well the response of the structure, this model is often a non-minimal realization (i.e., the dynamics of various modes are duplicated in the model); these extra dynamics can degrade the performance of the resulting controller. This paper presents a hybrid system identification approach that can result in minimal (or near-minimal) realizations of the MIMO structure–control system models that are effective for structural control design. The first step in this approach develops a simplified model which can portray adequately the system characteristics found in the experimental data. Using information about the pole–zero relationship of the transfer function in the simplified model, a frequency-domain system identification strategy is employed subsequently to derive multiple single-input and multiple-output (SIMO) models with respect to each system input. The systems are then combined to determine the complete MIMO system model that is accurate over the frequency range of interest for the control applications. To demonstrate this hybrid approach, an example is provided to illustrate a high-fidelity identification result from the experiment of an actively isolated building system. Successful control implementation demonstrates the efficacy of this hybrid system identification approach.

Reduced‐complexity performance‐lossless (quasi‐)maximum‐likelihood detectors for S‐QAM modulated MIMO systems

Proposed is a simplified branch metric calculation method for the (quasi-)maximum-likelihood (ML) detector for square quadrature amplitude modulation (S-QAM) aided multiple-input and multiple-output (MIMO) multiplexing systems while retaining identical performance to the respective one. The key idea of the proposed method is to exploit the geometric property of the S-QAM constellation, so that the branch metric calculation for all the constellation points can be calculated in an incremental way from any constellation point mainly through addition and bit-shift, thus significantly reducing the computational complexity of the ML detector.

Cross-layer Design for MIMO Systems with Transmit Antenna Selection and Imperfect CSI

In this paper, by combining adaptive modulation and automatic repeat request (ARQ), a cross-layer design (CLD) scheme for multiple-input and multiple-output (MIMO) system with transmit antenna selection (TAS) and imperfect channel state information (CSI) is presented. Based on the imperfect CSI, the probability density function of the effective signal to noise ratio (SNR) is derived, and the fading gain switching thresholds are also derived subject to a target packet loss rate and fixed power constraint. According to these results, we further derive the average spectrum efficiency (SE) and packet error rate (PER) of the system. As a result, closed-form expressions of the average SE and PER are obtained, respectively. The derived expressions include the expressions under perfect CSI as special cases, and can provide good performance evaluation for the CLD system with imperfect CSI. Simulation results verify the validity of the theoretical analysis. The results show that the CLD system with TAS provides better SE than that with space-time block coding, but the SE and PER performance of the system with imperfect CSI are worse than those with perfect CSI due to the estimation error.

Average Mutual Information Analysis of Multiple Input and Multiple Output System with Multihop Relaying in Wireless Communication System

Problem statement: Multiple Input and Multiple Output (MIMO) system with Multihop relaying techhnique is significant and active areas of wireless communication. In a rich scattering environment MIMO antenna system provides better channel capacity and data rates than single antenna systems. To provide high throughput, reliable transmission and broad coverage, wireless relaying techniques are essential in a variety of applications. In a cellular environment a relay can be used to overcome shadowing effect due to obstacles and multihop relaying can improve the throughput for mobiles suffering from poor signal to interference, noise ratio at the edge of a cell and reduce cell size to increase spectral efficiency. Approach: This study analyzes average mutual information of the Ricean channel for single hop Multiple Input Multiple Output (MIMO) system for different antenna configuation and dependence of capacity on the Rice factor for cellular system. The asymptotic capacity of multiuser two-hop MIMO system with Regularization Block Diagonalization (RBD) precoding techniques for Indepenent Identically Distributed (IID) channal and realistic Mobile to Mobile fading channel model was examined. In this realistic model, Non-Line-Sight (NLOS) propagation conditions are assumed from source mobile station to mobile relay and also from mobile relay to destination station. A non regenerative Amplify and Forward (AF) relay is used to optimize the capacity between the source and destination and also the evaluation was made for multiuser multi-hop relay system with correlated fading channel model using RBD precoding matrix. Results: The simulation results for average mutual information of single hop MIMO relay system for different antenna configuration with ricean channel model, ergodic sum mutual information for two hop relay system with RBD precoding technique and mutual information results for multiuser multihop relay system with correlated channel model was presented. Conclusion/Recommendations: Cellular systems generally operated at a fairly low SINR which can be increased on each hop by adding relays. Multiuser two hop relay system with RBD precoding for realistic mobile to mobile fading channel model is simulated and compared with IID channel model. Multiuser Multi-hop relay with optimal precoding and RBD precoding technique results were analyzed for correlated fading channel and found that capacity offered by RBD precoding scheme is better than other relaying systems.

Visualization maps based on SOM to analyze MIMO systems

Knowledge extraction from large amounts of data is an effective approach for analysis and monitoring of industrial processes. The self-organizing map (SOM) is a useful method for this purpose, because it is able to discover low-dimensional structures on high-dimensional spaces and produce a mapping on an ordered low-dimensional space that can be visualized and preserves the most important relationships. With the aim to extract knowledge about the dynamics of industrial processes, we define 2D SOM maps that represent dynamic features which are useful for usual tasks in control engineering such as the analysis of the time response, the coupling among variables, or the difficulties in control of MIMO (multiple-input and multiple-output) systems. Those new maps make it possible to discover, increase or confirm knowledge about the system, spanned through the entire operation range. A well-known quadruple-tank MIMO system was used to test the usefulness of these maps. First, we perform an analysis of the theoretical dynamic behaviors obtained from the physical equations of the system. After that, we carry out an analysis of experimental data from an industrial pilot plant.

A FRACTIONAL ORDER UNIVERSAL HIGH GAIN ADAPTIVE STABILIZER

In this paper, a fractional order universal high gain adaptive stabilizer is proposed which guarantees the Lp stability of fractional order multiple–input and multiple–output (MIMO) systems with finite control effort. The boundedness of the control gain for the fractional order universal adaptive strategy is discussed for fractional order MIMO systems, and an upper bound of the control gain is presented for fractional order single-input and single-output (SISO) systems. Some advantages of the discussed fractional order universal adaptive stabilizer are demonstrated in numerical simulations, such as the overshoots of system outputs can be efficiently reduced by decreasing the fractional order of the universal adaptive stabilizer without significantly increasing the system gains.

Nonlinear inversion-based control with adaptive neural network compensation for uncertain MIMO systems

A robust output feedback control scheme for uncertain nonlinear multiple-input and multiple-output (MIMO) systems is proposed, which combines a nonlinear inversion-based controller with a neural network-based robust compensator. The nonlinear inversion-based controller acts as the main controller, and a neural network with an adaptive update law is designed to model the unknown system dynamics, a variable structure controller is employed to eliminate the effect of the neural network approximation errors and to ensure the system stability. Furthermore, an H∞ controller which is a component of the robust compensator is designed to achieve a certain robust tracking performance and to attenuate the effect of external disturbances to a prescribed level. The proposed approach indicates that the nonlinear inversion-based control method is also valid for controlling uncertain nonlinear MIMO systems with uncertainties and disturbances, provided that a compensative controller is designed appropriately. Simulation results demonstrated that the proposed controller performed better in comparison to the nonlinear inversion-based control method and an advanced neural network-based hybrid controller.

Adaptive equalization for high speed optical MIMO wireless communications using white LED

Light emitting diode (LED) is one of the most important light sources in the 21st century and has broad prospects in the illumination. Currently, the white LED is used not only for illumination, but also for transmission data. A new technique referred as visible light communication (VLC) is rapidly growing in optical communication. In order to enhance the performance of the communication link, we present optical multiple input and multiple output (MIMO) communication system to achieve high data rate, which can mitigate the shadow effect of indoor communication. Moreover, the MIMO will bring about multi-path effect, which causes inter-symbol interference (ISI) to degrade the performance of the link. Hence, an adaptive equalization technique has been used in the receiver system, which can reduce the ISI when the system is determined to receive symbol. Finally, we have simulated the MIMO system with adaptive equalization. The simulation results show significant improvement in the transmission rate using on off keying (OOK) and the average signal to noise ratio (SNR) in this channel has increased 13.5 dB after equalization.

Distributed Cooperative Precoding with SINR-Based Co-Channel User Grouping for Enhanced Cell Edge Performance

We consider the problem of cooperative precoding for controlling interference in the downlink of a multiple-input and multiple-output (MIMO) interference channel. A model for the multicell, multiuser, MIMO system is analyzed, and a criterion to simultaneously maximize the SINRs of users sharing a common spectral resource is provided. An asymptotically optimal solution is then proposed as the number of users per sector (U) and the number of resources (B) in the system become large, within a specific framework for scheduling co-channel users in interfering cells. Based on this, a heuristic algorithm for distributed cooperative precoder selection (CPS) is proposed for application in practical systems with finite B and U values. System performance gains measured in terms of mean cell throughput and cell-edge spectral efficiency values are estimated using numerical simulations. The proposed technique takes into account practical constraints such as limiting the information exchanged from the user equipments to the serving base stations, and amongst the cooperating base stations, to a modest level.

Spatio-temporal channel characterization: theoretical framework and applications in MIMO system design

The utilization of multiple antennas and space–time codes in multiple-input and multiple-output (MIMO) communication systems significantly improves the transmission channel capacity without using additional bandwidth and power. The improvement is achieved by decomposing the spatial structure of transmission channels and performing appropriate temporal and spatial multiplexing. In this paper, we propose a novel theoretical framework for MIMO channel modeling and characterization in order to facilitate the MIMO system design and performance evaluation. The channels are represented in space, time, wave vector, and frequency domains while the space–time and wave vector–frequency interdependences are considered. A realization of the theoretical framework, in a form of a practical framework, is also proposed to address the channel modeling and characterization at both transmitter and receiver sides. The utilization of the practical framework in MIMO communication system design is discussed to illustrate its applications in realistic scenarios. The angle of arrival estimation based on the proposed practical framework using field test measurement data is also presented as illustrative examples.

Cooperative Diversity in Wireless Networks

Transmit Diversity is an effective methodology for improving the quality and reliability of a wireless network by reducing the effects of fading. As majority of the wireless devices (i.e. mobile handsets, etc) are limited to only one antenna, especially due to hardware constraints, size and cost factors; cooperative communication can be utilized in order to generate transmit diversity [1]. This enables single antenna wireless devices to share their antennas during transmission in such a manner that creates a virtual MIMO (multiple-input and multiple-output) system [2] [3]. In this paper, we will analyze the recent developments and trends in this promising area of wireless Ad hoc networks. The article will also discuss various main cooperative signaling methods and will also observe their performance.

Approaching MIMO capacity using bitwise Markov Chain Monte Carlo detection

This paper examines near capacity performance of Markov Chain Monte Carlo (MCMC) detectors for multiple-input and multiple-output (MIMO) channels. The proposed MCMC detector (Log-MAP-tb b-MCMC) operates in a strictly bit-wise fashion and adopts Log-MAP algorithm with table look-up. When concatenated with an optimized low-density parity-check (LDPC) code, Log-MAP-tb b-MCMC can operate within 1.2-1.8 dB of the capacity of MIMO systems with 8 transmit/receive antennas at spectral efficiencies up to ¿ = 24 bits/channel use (b/ch). This result improves upon best performance achieved by turbo coded systems using list sphere decoding (LSD) detector by 2.3-3.8 dB, leading to nearly 50% reduction in the capacity gap. Detailed comparisons of the Log-MAP-tb b-MCMC with LSD based detectors demonstrate that MCMC detector is indeed the detector of choice for achieving channel capacity both in terms of performance and complexity.

Geodesical Codebook Design for Precoded MIMO Systems

We propose a numerical method for finding packings of multiple-input and multiple-output (MIMO) semi-unitary precoding matrices in Grassmannian manifolds with different metrics. The proposed expansion-compression algorithm (ECA) is practical, simple and produces efficient packings without the need for a sophisticated initialization. With chordal distance metric, the algorithm tends to converge into a degenerated point constellation, where two points contain identical as well as orthogonal columns and distance between them cannot increase further along geodesic. Therefore, we alternate between max-min and min-max clustering parts of ECA algorithm, where the latter prevents degenerated constellations. With Fubini-Study distance metric, the algorithm converges to best known packings without extra min-max processing.

An Enhanced Double MEWMA Controller for Drifted MIMO Systems

For a drifted multiple-input and multiple-output (MIMO) system, the double multivariate exponentially weighted moving average (dMEWMA) controller is a popular run-to-run (RTR) controller for adjusting the process mean to a desired target. The stability and performance of dMEWMA controller had been widely studied in literature. Although the dMEWMA controller (with suitable discount matrices) can guarantee long-term stability, it usually requires a moderately large number of runs to bring the process output to approach its desired target if the initial recipe is not chosen appropriately. Due to the initial recipe possibly having an infinite number of feasible solutions for MIMO systems, “how to determine an optimal setting for the initial recipe” turns out to be an interesting research topic. In this article, by solving a constrained optimization problem, we first obtain an optimal initial setting for the input recipe. Then, motivated by this setting, we propose an enhanced dMEWMA controller. The long-term stability conditions and short-term performance of the proposed controller are also addressed. Given a fixed and finite production run, it reveals that the proposed controller has the ability of reducing total mean squared error (TMSE) better than the conventional dMEWMA controller.

Asymptotic Analysis of Outage Region in CDMA MIMO Systems

Uplink code-division multiple access (CDMA) multiple-input and multiple-output (MIMO) systems are considered in the large system limit within the assumptions of synchrony and frequency flat fading. The outage region maximizing the sum capacity of non-outage users is obtained, which extends the criterion of outage in single-input and single-output (SISO) CDMA systems.

Pre-Whitening QR-Decomposition Maximum Likelihood Detection for Co-channel Interference Rejection in MIMO Systems

We describe a co-channel interference rejection scheme that is suitable for QR-decomposition maximum likelihood detection (MLD) in multiple-input and multiple output (MIMO) systems. A pre-whitening matrix for interference rejection is decomposed into a triangular matrix and its Hermitian matrix by using a complex Gaxpy version of the Cholesky algorithm. The decomposed triangular matrix is used as a spatial pre-filter to whiten co-channel interference. Simulation results demonstrate that the proposed scheme can suppress co-channel interference streams at the cost of receive diversity order and achieves better transmission performance than QR-decomposition MLD itself in MIMO channels with co-channel interference.