Multiple-input And Multiple-output Systems Research Articles

Analysis for MIMO correlated frequency-selective channel in the presence of interference

The space time spreading, superimposed training sequences, and space-time coding are used to presenta multiple input and multiple output (MIMO) systems model, and a closed-form of average error probability up-per bound expression for MIMO correlated frequency-selective channel in the presence of interference (co-channelinterference and jamming signals) is derived. Moreover, the correlation at both ends of the wireless link that canbe incorporated equivalently into correlation at the transmit end is also derived, which is significant to analyzespace-time link algorithm of MIMO systems.

Design and analysis of bit interleaved coded space-time modulation

Bit interleaved coded space-time modulation (BIC- STM) is an attractive strategy to achieve high power- and bandwidth-efficiency over multiple-input and multiple-output (MIMO) fading channels due to coding and diversity gains promised by the serial concatenation of an outer convolutional code, a bitwise interleaver and an inner high order space-time modulation (STM). In this paper, BICSTM with iterative decoding (BICSTM-ID) including non-iterative decoding as a special case is considered. For designing the inner STM, two parameters based on bitwise pairwise error probabilities (b- PEP) for the cases with and without a-priori knowledge are proposed as new measures for designing labeling rules for the STM codewords set suited to iterative decoding. On the other hand, the BICSTM-ID scheme is analyzed from an information theoretical aspect, and Information Processing Characteristic (IPC) analysis is developed for MIMO systems in order to fully characterize the BICSTM-ID scheme based on a new equivalent model of combined binary input channels. The analysis results show that the IPC analysis offers a unified perspective for BICSTM and BICSTM-ID from an information theoretical point of view and provides a comprehensive insight into the whole BICSTM-ID scheme as well. Additionally, IPC based upper and lower bounds on bit error ratio (BER) performance are extended to BICSTM-ID, and are confirmed by simulations. These bounds are of significant practical interest for estimating the BER performance of the bit-interleaved concatenated schemes with general nonlinear inner systems.

Stability and performance of a double MEWMA controller for drifted MIMO systems

Many semiconductor manufacturing processes have, by nature, Multiple-Input and Multiple-Output (MIMO) variables. For a drifted MIMO process, the double Multivariate Exponentially Weighted Moving Average (dMEWMA) controller is a popular run-to-run controller for adjusting the process mean to a desired target. The stability conditions of a dMEWMA controller have received considerable attention in the literature. There are two limitations in the existed literature. First, these approaches only demonstrate that the asymptotic mean will meet a desired target; however, they do not show that mean square error matrix for a process is bounded. Second, they do not have an explicit expression of the process output of the dMEWMA controller for any production run t. Hence, by using a conventional state space formulation, it is impossible to address the process performance (such as process fallout rate of the dMEWMA controller) analytically. Using a different approach, this paper derives an analytical expression for the process output of a dMEWMA controller. The problems of the stability conditions and the performance of the dMEWMA controller can then be addressed successfully.

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.

Sample Size Determination for Achieving Stability of Double Multivariate Exponentially Weighted Moving Average Controller

Many semiconductor manufacturing processes have by nature multiple-input and multiple-output (MIMO) variables. For the first-order MIMO process with a linear drift, the double multivariate exponentially weighted moving average (dMEWMA) controller is a popular run-to-run (R2R) controller for adjusting the process mean to a desired target. The long-term stability of this closed-loop MIMO system has not yet been thoroughly investigated and is the focus of our present study. The stability of this MIMO system using a controller with estimated process parameters depends on whether an initial input–output (I–O) predicted model can be obtained successfully in advance (i.e., offline) to accurately and precisely estimate these process parameters. However, the predicted model is typically constructed during an offline DOE/RSM stage, based on a random sample from the I–O variables, and thus the sample size and the strength of the linear relationship between I–O variables play major roles in determining the stability of the process. In this article we first obtain the stability conditions for the MIMO process. Obviously, these conditions depend on the estimated controller, and, consequently, one of the conditions is expressed in terms of a probability. We then derive a formula for the adequate sample size required to achieve stability for the closed-loop MIMO system with a guaranteed probability. We also describe how the offline DOE/RSM is conducted to obtain process parameter estimates. We give two practical MIMO examples to illustrate the proposed procedure. Finally, we describe a study demonstrating the impact of the covariance structure of I–O variables on the required sample size.

Pre-DFT Processing for MIMO-OFDM Systems with Space-Time-Frequency Coding

Subcarrier based space processing was conventionally employed in Orthogonal Frequency Division Multiplexing (OFDM) systems under Multiple-Input and Multiple-Output (MIMO) channels to achieve optimal performance. At the receiver of such systems, multiple Discrete Fourier Transform (DFT) blocks, each corresponding to one receive antenna, are required to be used. This induces considerable complexity. In this paper, we propose a pre-DFT processing scheme for the receiver of MIMO-OFDM systems with space-time-frequency coding. With the proposed scheme, the number of DFT blocks at the receiver can be any number from one to the number of receive antennas, thus enabling effective complexity and performance tradeoff. Using the pre-DFT processing scheme, the number of input signals to the space-time-frequency decoder can be reduced compared with the subcarrier based space processing. Therefore, a high dimensional MIMO system can be shrunk into an equivalently low dimension one. Due to the dimension reduction, both the complexity of the decoder and the complexity of channel estimation can be reduced. In general, the weighting coefficients calculation for the pre-DFT processing scheme should be relevant to the specific space-time-frequency code employed. In this paper, we propose a simple universal weighting coefficients calculation algorithm that can be used to achieve excellent performance for most practical space-time-frequency coding schemes. This makes the design of the pre-DFT processing scheme independent of the optimization of the space-time-frequency coding, which is desirable for multiplatform systems.

Frequency Domain Realization of Space-Time Receivers in Dispersive Wireless Channels

In this paper, we present a class of low complexity space-time receivers for frequency-selective channels in multiple input and multiple output (MIMO) systems. The main idea is that under certain conditions the matrices involved in the implementation of linear and nonlinear equalizers for MIMO systems can be approximated with block circulant matrices which can be inverted via block DFT operations. As result, the computational complexity of the receiver implementation is drastically reduced. First, we extend to MIMO systems two linear approaches originally derived in the framework of joint detection techniques for code division multiple access. Next, we develop a hybrid zero-forcing block decision feedback equalizer (DFE) and a minimum mean square error block DFE for MIMO systems, by performing in the frequency domain the feedback processing as in Benvenuto and Sostrato and the block linear equalizer as in Vollmer , while interference cancellation is performed in the time domain. Last, we extend to the frequency domain the fully connected ordered successive interference cancellation DFE. We show that these receivers yield almost the same performance as the original space-time receivers implemented in the time domain, and their computational complexity is lower, even against state of the art fast time-domain realizations

Energy spreading transform based iterative signal detection for mimo fading channels

Multiple transmit and receive antenna arrays can be used to form multiple input and multiple output (MIMO) systems for diversity and multiplexing in wireless communications. In this paper, we develop iterative signal-detection schemes based on energy spreading transform (EST) (T. Hwang and Y. Li) for MIMO channels. The EST in a MIMO system improves signal-detection performance by spreading the symbol energy over the space and time domain. It also enables iterative signal detection without employing channel coding. Analytical and simulation results demonstrate that the performance of the proposed schemes is very close to that of the genie-aided receiver when there are a sufficiently large number of receive antennas and signal-to-noise ratio (SNR) is above a threshold

Practical generalized predictive control with decentralized identification approach to HVAC systems

A practical generalized predictive control strategy with novel parameter identification method from step test for multiple inputs and multiple outputs (MIMO) systems is presented in this paper. Through sequential step changes of set points, the coupled closed loop MIMO system is decoupled equivalently into four individual single open loop processes with the same input signal acting on the four transfer functions. On the basis of an identification model, the proposed controller with low computation and simple structure is very suitable for typical process control systems. Based on a HVAC plant, simulations results demonstrate the above conclusions.

Performance Enhancement of MLD with Parallel Interference Canceller by Unequal-Power Transmission in MIMO Systems

This letter describes unequal-power transmission for multiple-input and multiple-output (MIMO) systems with a parallel interference canceller (PIC) applied to a maximum likelihood detector (MLD) or complexity-reduced MLD at the receiver. Unequal-power transmission reduces the possibility that all substreams are incorrectly decoded. Canceling the correctly decoded substreams enables more reliable detection in the next stage. The simulation results demonstrated that unequal-power transmission improves the transmission performance of the PIC applied to MLDs or complexity-reduced MLDs, compared with equal-power transmission cases.

Capacity of Noncoherent Time-Selective Rayleigh-Fading Channels

The capacity of noncoherent time-selective Rayleigh-fading channels is studied under various models for the variations in time. The study includes both single-input and single-output (SISO) and multiple-input and multiple-output (MIMO) systems. A block-fading model is first considered where the channel changes correlatively over each block period of length T, and independently across blocks. The predictability of the channel is characterized through the rank Q of the correlation matrix of the vector of channel gains in each block. This model includes, as special cases, the standard block-fading model where the channel remains constant over block periods (Q=1), and models where the fading process has finite differential entropy rate (Q=T). The capacity is initially studied for long block lengths and some straightforward but interesting asymptotes are established. For the case where Q is kept fixed as T/spl rarr//spl infin/, it is shown that the noncoherent capacity converges to the coherent capacity. For the case where both T,Q/spl rarr//spl infin/, with Q/T being held constant, a bound on the capacity loss due to channel unpredictability is established. The more interesting scenario of large signal-to-noise ratio (SNR) is then explored in detail. For SISO systems, useful upper and lower bounds on the large SNR asymptotic capacity are derived, and it is shown that the capacity grows logarithmically with SNR with a slope of T-Q/spl rarr/T, for Q<T. Next, in order to facilitate the analysis of MIMO systems, the rank-Q block-fading model is specialized to the case where each T-symbol block consists of Q subblocks of length L, with the channel remaining constant over each subblock and changing correlatively across subblocks. For this model, it is shown that the log SNR growth behavior of the capacity is the same as that of the standard block-fading model with block length L. Finally, the SISO and MIMO channel models are generalized to allow the fading process to be correlated across blocks in a stationary and ergodic manner. It is shown that the log SNR growth behavior of the capacity is not affected by the correlation across blocks.

Weighted Monte-Carlo experimental measurement and integrated data treatment

A weighted Monte-Carlo experimental measurement is proposed to simulate the random process behaviors of a large and complex MIMO (multiple-input and multiple-output) system. Trying to accurately describe the system with experimental data as little as possible, a method of integrated database with modified Interpolation and Lagrange Polynomial is developed. Although the research is initialized for empirically resolving the control of large and complex MIMO system, it also provides an effective and useful method of data reduction in general to meet the urgent needs of modern data acquisition and data treatment.

D-BLAST OFDM with Channel Estimation

Multiple-input and multiple-output (MIMO) systems formed by multiple transmit and receive antennas can improve performance and increase capacity of wireless communication systems. Diagonal Bell Laboratories Layered Space-Time (D-BLAST) structure offers a low-complexity solution for realizing the attractive capacity of MIMO systems. However, for broadband wireless communications, channel is frequency-selective and orthogonal frequency division multiplexing (OFDM) has to be used with MIMO techniques to reduce system complexity. In this paper, we investigate D-BLAST for MIMO-OFDM systems. We develop a layerwise channel estimation algorithm which is robust to channel variation by exploiting the characteristic of the D-BLAST structure. Further improvement is made by subspace tracking to considerably reduce the error floor. Simulation results show that the layerwise estimators require 1 dB less signal-to-noise ratio (SNR) than the traditional blockwise estimator for a word error rate (WER) of when Doppler frequency is 40 Hz. Among the layerwise estimators, the subspace-tracking estimator provides a 0.8 dB gain for WER with 200 Hz Doppler frequency compared with the DFT-based estimator.

Approaching near-capacity on a multi-antenna channel using successive decoding and interference cancellation receivers

In this paper, we address the problem of designing multirate codes for a multiple-input and multiple-output (MIMO) system by restricting the receiver to be a successive decoding and interference cancellation type, when each of the antennas is encoded independently. Furthermore, it is assumed that the receiver knows the instantaneous fading channel states but the transmitter does not have access to them. It is well known that, in theory, minimum-mean-square error (MMSE) based successive decoding of multiple access (in multi-user communications) and MIMO channels achieves the total channel capacity. However, for this scheme to perform optimally, the optimal rates of each antenna (per-antenna rates) must be known at the transmitter. We show that the optimal per-antenna rates at the transmitter can be estimated using only the statistical characteristics of the MIMO channel in time-varying Rayleigh MIMO channel environments. Based on the results, multirate codes are designed using punctured turbo codes for a horizontal coded MIMO system. Simulation results show performances within about one to two dBs of MIMO channel capacity.

Interference avoidance and multiuser MIMO systems

AbstractWe apply interference avoidance methods to multiuser systems with multiple inputs and multiple outputs (MIMO) such as would be used on the uplink (or in overlapping downlink footprints) for satellite systems with multiple antennas. An arbitrary signal space can be used and the method can be applied to any MIMO system model regardless of the choice signal basis functions. Information is transmitted via multicode CDMA where symbols that comprise the data frame from a given user are ‘spread’ over the available dimensions using a precoding matrix. Optimal precoding matrices that maximize signal‐to‐interference plus noise‐ratio for all symbols/users are then obtained by application of distributed greedy interference avoidance methods. In general, algorithms based on greedy interference avoidance are different from water filling schemes. However, the codeword ensembles obtained provide similar simultaneous water filling solutions and thus maximize sum capacity. Numerical simulations have been performed and the signal‐to‐noise ratio distribution for receiver antennas and complementary cumulative distribution functions for sum capacity with optimal precoding matrices are also presented. Copyright © 2003 John Wiley &amp; Sons, Ltd.