70 resultados para Multiple-input-multiple-output (mimo)


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Designing minimum possible order (minimal) disturbance-decoupled proper functional observers for multi-input multi-output (MIMO) linear time-invariant (LTI) systems is studied. It is not necessary that a minimum-order unknown-input functional observer (UIFO) exists in our proposed design procedure. If the minimum-order observer cannot be attained, the observer's order is increased sequentially through a recursive algorithm, so that the minimal order UIFO can be obtained. To the best of our knowledge, this is the first time that this specific problem is addressed. It is assumed that the system is unknown-input functional detectable, which is the least requirement for the existence of a stable UIFO. This condition also is a certificate for the convergence of our observer's order-increase algorithm. Two methodologies are demonstrated to solve the observer design equations. The second presented scheme, is a new design method that based on our observations has a better numerical performance than the first conventional one. Numerical examples and simulation results in the MATLAB/Simulink environment describe the overall observer design procedure, and highlight the efficacy of our new methodology to solve the observer equations in comparison to the conventional one.

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In this study, we proposed an adaptive fuzzy multi-surface sliding control (AFMSSC) for trajectory tracking of 6 degrees of freedom inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). It is shown that an adaptive fuzzy logic-based function approximator can be used to estimate the system uncertainties and an iterative multi-surface sliding control design can be carried out to control flight. Using AFMSSC on MIMO autonomous flight systems creates confluent control that can account for both matched and mismatched uncertainties, system disturbances and excitation in internal dynamics. It is proved that the AFMSSC system guarantees asymptotic output tracking and ultimate uniform boundedness of the tracking error. Simulation results are presented to validate the analysis.

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Functional observer design for Multi-Input Multi-Output (MIMO) Linear Time-Invariant (LTI) systems with multiple mixed time delays in the states of the system is addressed. Two structures for the design of a minimum-order observer are considered: 1 - delay-dependent, and 2 - internal-delay independent. The parameters of the delay-dependent observer are designed using the Lyapunov Krasovskii approach. The delay-dependent exponential stability of the observer for a specified convergence rate and delay values is guaranteed upon the feasibility of a set of Linear Matrix Inequalities (LMIs) together with a rank condition. Using the descriptor transformation, a modified Jensen's inequality, and improved Park's inequality, the results can be less conservative than the available functional observer design methods that address LTI systems with single state delay. Furthermore, the necessary and sufficient conditions of the asymptotic stability of the internal-delay independent observer are obtained, which are shown to be independent of delay. Two illustrative numerical examples and simulation studies confirm the validity and highlight the performance of the proposed theoretical achievements.

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This paper deals with the equalization of a nonirreducible multiple-input multiple-output (MIMO) finite-impulse-response (FIR) channel provided that the estimate of the channel matrix is available. An iterative method is developed to perform the channel equalization. The effectiveness of the proposed equalization method is demonstrated by simulation examples.

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In this chapter the authors discuss the physical insight of the role of wireless communication in RFID systems. In this respect, this chapter gives a brief introduction on the wireless communication model followed by various communication schemes. The chapter also discusses various channel impairments and the statistical modeling of fading channels based on the environment in which the RFID tag and reader may be present. The chapter deals with the fact that the signal attenuations can be dealt with up to some level by using multiple antennas at the reader transmitter and receiver to improve the performance. Thus, this chapter discusses the use of transmit diversity at the reader transmitter to transmit multiple copies of the signal. Following the above, the use of receiver combining techniques are discussed, which shows how the multiple copies of the signal arriving at the reader receiver from the tag are combined to reduce the effects of fading. The chapter then discusses various modulation techniques required to modulate the signal before transmitting over the channel. It then presents a few channel estimation algorithms, according to which, by estimating the channel state information of the channel paths through which transmission takes place, performance of the wireless system can be further increased. Finally, the Antenna selection techniques are presented, which further helps in improving the system performance.


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The optimal source precoding matrix and relay amplifying matrix have been developed in recent works on multiple-input multiple-output (MIMO) relay communication systems assuming that the instantaneous channel state information (CSI) is available. However, in practical relay communication systems, the instantaneous CSI is unknown, and therefore, has to be estimated at the destination node. In this paper, we develop a novel channel estimation algorithm for two-hop MIMO relay systems using the parallel factor (PARAFAC) analysis. The proposed algorithm provides the destination node with full knowledge of all channel matrices involved in the communication. Compared with existing approaches, the proposed algorithm requires less number of training data blocks, yields smaller channel estimation error, and is applicable for both one-way and two-way MIMO relay systems with single or multiple relay nodes. Numerical examples demonstrate the effectiveness of the PARAFAC-based channel estimation algorithm.

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In conventional two-phase channel estimation algorithms for dual-hop multiple-input multiple-output (MIMO) relay systems, the relay-destination channel estimated in the first phase is used for the source-relay channel estimation in the second phase. For these algorithms, the mismatch between the estimated and the true relay-destination channel affects the accuracy of the source-relay channel estimation. In this paper, we investigate the impact of such channel state information (CSI) mismatch on the performance of the two-phase channel estimation algorithm. By explicitly taking into account the CSI mismatch, we develop a robust algorithm to estimate the source-relay channel. Numerical examples demonstrate the improved performance of the proposed algorithm. © 2012 IEEE.

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In this paper, we integrate two blind source separation (BSS) methods to estimate the individual channel state information (CSI) for the source-relay and relay-destination links of three-node two-hop multiple-input multiple-output (MIMO) relay systems. In particular, we propose a first-order Z-domain precoding technique for the blind estimation of the relay-destination channel matrix, while an algorithm based on the constant modulus and mutual information properties is developed to estimate the source-relay channel matrix. Compared with training-based MIMO relay channel estimation approaches, our algorithm has a better bandwidth efficiency as no bandwidth is wasted for sending the training sequences. Numerical examples are shown to demonstrate the performance of the proposed algorithm. © 2014 IEEE.

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In this paper, we investigate the channel estimation problem for two-way multiple-input multiple-output (MIMO) relay communication systems in frequency-selective fading environments. We propose a superimposed channel training algorithm to estimate the individual channel state information (CSI) of the first-hop and second-hop links for two-way MIMO relay systems with frequency-selective fading channels. In this algorithm, a relay training sequence is superimposed on the received signals at the relay node to assist the estimation of the second-hop channel matrices. The optimal structure of the source and relay training sequences is derived to minimize the meansquared error (MSE) of channel estimation. We also derive the optimal power allocation between the source and relay training sequences. Numerical examples are shown to demonstrate the performance of the proposed algorithm.

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In this paper, we investigate the channel estimation problem for multiple-input multiple-output (MIMO) relay communication systems with time-varying channels. The time-varying characteristic of the channels is described by the complex-exponential basis expansion model (CE-BEM). We propose a superimposed channel training algorithm to estimate the individual first-hop and second-hop time-varying channel matrices for MIMO relay systems. In particular, the estimation of the second-hop time-varying channel matrix is performed by exploiting the superimposed training sequence at the relay node, while the first-hop time-varying channel matrix is estimated through the source node training sequence and the estimated second-hop channel. To improve the performance of channel estimation, we derive the optimal structure of the source and relay training sequences that minimize the mean-squared error (MSE) of channel estimation. We also optimize the relay amplification factor that governs the power allocation between the source and relay training sequences. Numerical simulations demonstrate that the proposed superimposed channel training algorithm for MIMO relay systems with time-varying channels outperforms the conventional two-stage channel estimation scheme.

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© 2002-2012 IEEE. In this paper, we investigate the channel estimation problem for two-way multiple-input multiple-output (MIMO) relay communication systems in frequency-selective fading environments. We apply the method of superimposed channel training to estimate the individual channel state information (CSI) of the first-hop and second-hop links for two-way MIMO relay systems with frequency-selective fading channels. In this algorithm, a relay training sequence is superimposed on the received signals at the relay node to assist the estimation of the second-hop channel matrices. The optimal structure of the source and relay training sequences is derived to minimize the mean-squared error (MSE) of channel estimation. Moreover, the optimal power allocation between the source and relay training sequences is derived to improve the performance of channel estimation. Numerical examples are shown to demonstrate the performance of the proposed superimposed channel training algorithm for two-way MIMO relay systems in frequency-selective fading environments.

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In this paper, we propose a blind channel estimation and signal retrieving algorithm for two-hop multiple-input multiple-output (MIMO) relay systems. This new algorithm integrates two blind source separation (BSS) methods to estimate the individual channel state information (CSI) of the source-relay and relay-destination links. In particular, a first-order Z-domain precoding technique is developed for the blind estimation of the relay-destination channel matrix, where the signals received at the relay node are pre-processed by a set of precoders before being transmitted to the destination node. With the estimated signals at the relay node, we propose an algorithm based on the constant modulus and signal mutual information properties to estimate the source-relay channel matrix. Compared with training-based MIMO relay channel estimation approaches, the proposed algorithm has a better bandwidth efficiency as no bandwidth is wasted for sending the training sequences. Numerical examples are shown to demonstrate the performance of the proposed algorithm.

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We address the blind equalization of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channel systems excited by constant modulus (CM) signals. It is known that the algorithms based on the CM criterion can equalize an FIR MIMO system that is irreducible. The irreducible condition is restrictive as it requires all source signals to be received at sensors simultaneously. In this paper, we further show that the CM property of signals can be exploited to construct a zero-forcing equalizer for a system that is nonirreducible. Simulation examples demonstrate the proposed result.

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We address the blind equalization of finite-impulse-response (FIR), multiple-input multiple-output (MIMO) channels excited by constant modulus (CM) signals. It is known that the algorithms based on the constant modulus (CM) criterion can equalize an FIR MIMO channel that is irreducible and column-reduced. We show in this paper that the CM property of signals can be exploited to construct a zero-forcing equalizer for a non-irreducible and non-column-reduced channel. We also give a lower bound for the order of the equalizer. Simulation examples demonstrate the proposed result.

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This paper deals with the problem of blind equalization of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channels excited by M-ary phase shift keying (MPSK) signals. It is known that the algorithms based on the constant modulus (CM) criterion can equalize an FIR MIMO channel that is irreducible. The irreducible condition is restrictive since it requires that all source signals arrive at the receiving antennas simultaneously. In this paper, we show that the CM criterion can also be used to construct a zero-forcing equalizer for a channel that is non-irreducible. We also derive a lower bound for the order of the equalizer. The proposed result is validated by numerical simulations.