Stabilization of fractional bilinear systems with multiple inputs

In this paper,we study in a constructive way the stabilization problem of fractional bilinear systems with multiple inputs.Using the quadratic Lyapunov functions and some additional hypotheses on the unit sphere,we construct stabilizing feedback laws for the considered fractional bilinear system.A numerical example is given to illustrate the efficiency of the obtained result.

Dynamic Consensus of High-order Multi-agent Systems and Its Application in the Motion Control of Multiple Mobile Robots

In this paper, the leader-following consensus problem for multi-agent linear dynamic systems is considered. All agents and leader have identical multi-input multi-output （MIMO） linear dynamics that can be of any order, and only the output information of each agent is delivered throughout the communication network. When the interaction topology is fixed, the leader-following consensus is attained by Ho~ dynamic output feedback control, and the sufficient condition of robust controllers is equal to the solvability of linear matrix inequality （LMI）. The whole analysis is based on spectral decomposition and an equivalent decoupled structure achieved, and the stability of the system is proved. Finally, we extended the theoretical results to the case that the interaction topology is switching. The simulation results for multiple mobile robots show the effectiveness of the devised methods.

Identification of multiple inputs single output errors-in-variables system using cumulant

A higher-order cumulant-based weighted least square（HOCWLS） and a higher-order cumulant-based iterative least square（HOCILS） are derived for multiple inputs single output（MISO） errors-in-variables（EIV） systems from noisy input/output data. Whether the noises of the input/output of the system are white or colored, the proposed algorithms can be insensitive to these noises and yield unbiased estimates. To realize adaptive parameter estimates, a higher-order cumulant-based recursive least square（HOCRLS） method is also studied. Convergence analysis of the HOCRLS is conducted by using the stochastic process theory and the stochastic martingale theory. It indicates that the parameter estimation error of HOCRLS consistently converges to zero under a generalized persistent excitation condition. The usefulness of the proposed algorithms is assessed through numerical simulations.

Shannon information capacity of time reversal wideband multiple-input multiple-output system based on correlated statistical channels

Utilizing channel reciprocity, time reversal（TR） technique increases the signal-to-noise ratio（SNR） at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output（MIMO） communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems.

Channel capacity of multiple-input multiple-output systems with transmit and receive correlation

In order to investigate the impact of channel model parameters on the channel capacity of a multipleinput multiple-output （MIMO） system, a novel method is proposed to explore the channel capacity under Rayleigh fiat fading with correlated transmit and receive antennas. The optimal transmitting direction which can achieve maximum channel capacity is derived using random matrices theory. In addition, the closed-form expression for the channel capacity of MIMO systems is given by utilizing the properties of Wishart distribution when SNR is high. Computer simulation results show that the channel capacity is maximized when the antenna spacing increases to a certain point, and furthermore, the larger the scattering angle is, the more quickly the channel capacity converges to its maximum. At high SNR （〉12 dB）, the estimation of capacity is close to its true wlue. And, when the same array configuration is adopted both at the transmitter and the receiver, the UCA yields higher channel capacity than ULA.

Embedded Programmable Single Point Multiple Output Intelligent Data Acquisition and Transmission System

To effectively solve the problems of inconsistent communication protocols in automatic monitoring equipment,and limited data acquisition transmission and monitoring equipment,this paper developed programmable single point multiple output intelligent data acquisition and transmission system. It made an in-depth elaboration of the data acquisition and transmission system from hardware design,software architecture and principle,main functions and technical parameters. Finally,it came up with four innovation points:(i) intelligent(automatic)matching a variety of communication protocols for environmental monitoring equipment,(ii) realizing multi-protocol and multi-target parallel data transmission,(iii) realizing remote dynamic input of control instructions through wired or wireless network,and(iv) supporting configuration(process) simulation of field equipment DCS operating conditions.

Switching between multiplexing and diversity in MIMO systems with QoS provisioning

Multiple-input multiple-output (MIMO) wireless communication systems can significantly improve the spectrum efficiency or transmission reliability through spatial multiplexing or diversity respectively.Most of previous works mainly have focused on the multiplexing-diversity tradeoff or switching between multiplexing and diversity without considering the property of heterogeneous QoS provisioning.In this paper,switching between multiplexing and diversity in MIMO system with the heterogeneous QoS provisioning is studied.Firstly the QoS provisioning for users are classified into two classes:users with real time service requirement and users with non-real time service requirement respectively.Then based on the heterogeneous QoS Provisioning for users,two different switching criterions are proposed,switching based on the Euclidean distance for users with real time service to minimize the probability of symbol error and capacity-based switching criterion for users with non-real time service to maximize the transmission capacity respectively.Finally,numerical simulation results are illustrated to demonstrate the performance of proposed scheme.

Dual Mode-Multiple Output SEPIC Converter Integrated with Passive Ripple Cancelling Circuit for Standalone PV Energy Harvesting System

This document addresses an exhaustive standalone Photovoltaic (PV) energy harvesting system considering two crucial issues: system efficiency and cost effectiveness. It contributes a compact resolution with a combined feature of Dual Mode-Multiple Output (DMMO) associated with input ripple reduction technique. Control strategy incorporates with aspect of Maximum Power Point Tracking (MPPT) and output voltage levels regulation. A theoretical analysis is conducted to evaluate the effect of ripple current on PV power. Proposed dual mode converter achieves efficiency of 98.36% and 97.76% respectively for mode-1 and mode-2 operation. However, simulation is performed applying MATLAB/SIMULINK tools to analyze the feasibility of the recommended system.

Defected Ground Structure Multiple Input-Output Antenna For Wireless Applications

In this paper,the investigation of a novel compact 2×2,2×1,and 1×1 Ultra-Wide Band(UWB)based Multiple-Input Multiple-Output(MIMO)antenna with Defected Ground Structure(DGS)is employed.The proposed Electromagnetic Radiation Structures(ERS)is composed of multiple radiating elements.These MIMO antennas are designed and analyzed with and without DGS.The feeding is introduced by a microstrip-fed line to significantly moderate the radiating structure’s overall size,which is 60×40×1 mm.The high directivity and divergence characteristics are attained by introducing the microstripfed lines perpendicular to each other.And the projected MIMO antenna structures are compared with others by using parameters like Return Loss(RL),Voltage Standing Wave Ratio(VSWR),Radiation Pattern(RP),radiation efficiency,and directivity.The same MIMO set-up is redesigned with DGS,and the resultant parameters are compared.Finally,the Multiple Input and Multiple Output Radiating Structures with and without DGS are compared for result considerations like RL,VSWR,RP,radiation efficiency,and directivity.This projected antenna displays an omnidirectional RP with moderate gain,which is highly recommended for human healthcare applications.By introducing the defected ground structure in bottom layer the lower cut-off frequencies of 2.3,4.5 and 6.0 GHz are achieved with few biological effects on radio propagation in human body communications.The proposed design covers numerous well-known wireless standards,along with dual-function DGS slots,and it can be easily integrated into Wireless Body Area Networks(WBAN)in medical applications.This WBAN links the autonomous nodes that may be situated either in the clothes,on-body or beneath the skin of a person.This system typically advances the complete human body and the inter-connected nodes through a wireless communication channel.

Efficient Graph-based Genetic Programming Representation with Multiple Outputs

In this work, we explore and study the implication of having more than one output on a genetic programming （GP） graph-representation. This approach, called multiple interactive outputs in a single tree （MIOST）, is based on two ideas. First, we defined an approach, called interactivity within an individual （IWI）, which is based on a graph-GP representation. Second, we add to the individuals created with the IWI approach multiple outputs in their structures and as a result of this, we have MIOST. As a first step, we analyze the effects of IWI by using only mutations and analyze its implications （i.e., presence of neutrality）. Then, we continue testing the effectiveness of IWI by allowing mutations and the standard GP crossover in the evolutionary process. Finally, we tested the effectiveness of MIOST by using mutations and crossover and conducted extensive empirical results on different evolvable problems of different complexity taken from the literature. The results reported in this paper indicate that the proposed approach has a better overall performance in terms of consistency reaching feasible solutions.

Improved List Sphere Decoder for Multiple Antenna Systems

An improved list sphere decoder （ILSD） is proposed based on the conventional list sphere decoder （LSD） and the reduced- complexity maximum likelihood sphere-decoding algorithm. Unlike the conventional LSD with fixed initial radius, the ILSD adopts an adaptive radius to accelerate the list cdnstruction. Characterized by low-complexity and radius-insensitivity, the proposed algorithm makes iterative joint detection and decoding more realizable in multiple-antenna systems. Simulation results show that computational savings of ILSD over LSD are more apparent with more transmit antennas or larger constellations, and with no performance degradation. Because the complexity of the ILSD algorithm almost keeps invariant with the increasing of initial radius, the BER performance can be improved by selecting a sufficiently large radius.

Impact of channel estimation error on channel capacity of multiple input multiple output system

In order to investigate the impact of channel estimation error on channel capacity of multiple input multiple output (MIMO) system, a novel method is proposed to explore the channel capacity in correlated Rayleigh fading environment. A system model is constructed based on the channel estimation error at receiver side. Using the properties of Wishart distribution, the lower bound of the channel capacity is derived when the MIMO channel is of full rank. Then a method is proposed to select the optimum set of transmit antennas based on the lower bound of the mean channel capacity. The novel method can be easily implemented with low computational complexity. The simulation results show that the channel capacity of MIMO system is sensitive to channel estimation error, and is maximized when the signal-to-noise ratio increases to a certain point. Proper selection of transmit antennas can increase the channel capacity of MIMO system by about 1 bit/s in a flat fading environment with deficient rank of channel matrix.

Exact controllability of rational expectations model with multiplicative noise and input delay

This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.

QSM-IDM -A novel quadrature spatial modulation based on interleaving division multiplexing for multiple antenna system

Quadrature Spatial Modulation (QSM) is a high spectral efficiency Multiple-Input Multiple Output (MIMO) technique used to improve the spectral efficiency of wireless communication systems. The main concept of QSM is to extend the spatial constellation of the conventional Spatial Modulation (SM) in both the in-phase and quadrature components of the data symbol. In this paper, because QSM-based on Interleaxdng Division Multiplexing (IDM) has not been introduced in the literature as a multiple antenna system, we introduced a novel scheme, called QSM system based on Interleaving Division Multiplexing (QSM-IDM). The antenna sets are also applied to a spreader, before being used to assign an antenna number for information transmission. Analysis and simulations for a flat fading channel show that the proposed QSM-IDM method significantly outperforms the original QSM system with the same data rate, while maintaining a relatively acceptable complexity. The obtained simulation results show that the conducted analysis yields significant improvements for the accuracy of the proposed scheme, with satisfactory complexity.

Variations in Tomotherapy Beam Outputs: A Multiple-Institutional Investigation

This study aimed to determine variations in tomotherapy beam outputs at multiple institutions. Measurements were obtained at 22 radiotherapy institutions. The first parameter was the absolute dose to water (Dfmsrw, Qmsr) in the machine-specific reference field (fmsr), which indicated a static field in the tomotherapy reference conditions defined by the International Atomic Energy Agency (IAEA) study group. The second measured parameter was the difference between the measured and the planed doses in the intensity modulated radiotherapy (IMRT) verification plans, which were created using a solid phantom by the vendor during tomotherapy apparatus installation to adjust the beam output. The IMRT verification plan error at each institution was defined as the systematic error of the beam output;Dfmsrw, Qmsr was subsequently modified. The Dfmsrw, Qmsr values of four institutions with a modified energy fluence per ideal open time (EFIOT) were lower than the values at other institutions. The mean value of all institutions except those four was 0.994 ± 0.013 Gy (range: 0.974 Gy, 1.017 Gy). When the Dfmsrw, Qmsr value was corrected by the IMRT verification error, this variation decreased. In addition, the mean IMRT verification errors in the TomoDirectTM and TomoHelicalTM modes with the TomoEDGETM mode were 1.2% ± 0.8% (range: -0.6%, 1.8%) and 0.2% ± 0.5% (range: -0.6%, 0.9%), respectively (p

Design of integrated radar and communication system based on MIMO-OFDM waveform

Orthogonal frequency division multiplexing (OFDM) waveform enables radar and communication functions simultaneously, which encounters low angle resolution and poor data rate for traditional single input single output (SISO) systems. To solve these problems, an integrated radar and communication system (IRCS) with multiple input multiple output (MIMO) OFDM waveform is proposed. The different limitations of radar and communication in designing such a system are investigated. Then, an optimization problem is devised to obtain suitable system parameters, including the number of subcarriers, subcarrier spacing, number of symbols, pulse repetition frequency (PRF) and length of cyclic prefix (CP). Finally, to satisfy the requirements of both radar and communication, the IRCS parameters are derived in three typical cases. Several numerical results are presented to illustrate the demands of radar and communication, inconsistent or consistent, for the IRCS parameters and the superiority of the proposed system.

Target estimation using MIMO radar with multiple subcarriers

This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. How the number of subcarriers in- fluences the estimation accuracy is illustrated by considering the joint Cramer-Rao bound and the mean square error of the maxi- mum likelihood estimate. The non-coherent MIMO radar ambiguity function with multiple subcarriers is developed and investigated by changing the number of subcarriers, the pulse width and the frequency spacing between adjacent subcarriers. The numerical results show that more subcarriers mean more accurate estimates, higher localization resolution, and larger pulse width results in a worse performance of target location estimation, while the fre- quency spacing affects target location estimation little.

Hybrid Precoder and Combiner Design with Finite Resolution PSs for mmWave MIMO Systems

Hybrid precoding and combining have been considered as a promising technology, which can provide a compromise between hardware complexity and system performance in millimeter wave multiple-input multiple-output systems. However, most existing hybrid precoder and combiner designs generally assume that infinite resolution phase shifters(PSs) are used to produce the analog beamformers. In a practical scene, the design with accurate PSs can lead to high hardware cost and power consumption. In this paper, we investigate the hybrid precoder and combiner design with finite resolution PSs in millimeter wave systems. We employ alternate optimization as the main strategy to jointly design analog precoder and combiner. In addition, we propose a low complexity algorithm, where the analog beamformers are implemented only by finite resolution PSs to maximize spectral efficiency. Then, the digital precoder and combiner are designed based on the obtained analog beamformers to improve the spectral efficiency. Finally, simulation results and mathematical analysis show that the proposed algorithm with low-resolution PSs can achieve near-optimal performance and have low complexity.

Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning

This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.