Showing papers on "MIMO published in 2000"

Space-time block codes: a capacity perspective

Abstract: Space-time block codes are a remarkable modulation scheme discovered recently for the multiple antenna wireless channel. They have an elegant mathematical solution for providing full diversity over the coherent, flat-fading channel. In addition, they require extremely simple encoding and decoding. Although these codes provide full diversity at low computational costs, we show that they incur a loss in capacity because they convert the matrix channel into a scalar AWGN channel whose capacity is smaller than the true channel capacity. In this letter the loss in capacity is quantified as a function of channel rank, code rate, and number of receive antennas.

The finite-length multi-input multi-output MMSE-DFE

Abstract: A new theoretical framework is introduced for analyzing the performance of a finite length minimum-mean-square error decision feedback equalizer (MMSE-DFE) in a multi-input multi-output (MIMO) environment. The framework includes transmit and receive diversity systems as special cases and quantifies the diversity performance improvement as a function of the number of transmit/receive antennas and equalizer taps. Fast and parallelizable algorithms for computing the finite-length MIMO MMSE-DFE are presented for three common multi-user detection scenarios.

MIMO wireless channels: capacity and performance prediction

Abstract: We present a new model for multiple-input multiple-output (MIMO) outdoor wireless fading channels which is more general and realistic than the usual i.i.d. model. We investigate the channel capacity as a function of parameters such as the local scattering radius at the transmitter and the receiver, the distance between the transmit (TX) and receive (RX) arrays, and the antenna beamwidths and spacing. We point out the existence of "pin-hole" channels which exhibit low fading correlation between antennas but still have poor rank properties and hence low capacity. Finally we show that even at long ranges high channel rank can easily be obtained under mild scattering conditions.

A stochastic multiple-input-multiple-output radio channel model for evaluation of space-time coding algorithms

Abstract: A simple framework for Monte Carlo simulations of a multiple-input-multiple-output radio channel is proposed. The derived model includes the partial correlation between the paths in the channel, as well as fast fading and time dispersion. The only input parameters required for the model are the shape of the power delay spectrum and the spatial correlation functions at the transmit and receive end. Thus, the required parameters are available in the open literature for a large variety of environments. It is furthermore demonstrated that the Shannon capacity of the channel is highly dependent on the considered environment.

Simulation results for an interference-limited multiple-input multiple-output cellular system

Abstract: We describe a simulation study of a cellular system using multiple-input multiple-output (MIMO) antenna techniques along with adaptive modulation and aggressive frequency reuse. We show for the case of 3 transmit and 3 receive antennas, how much MIMO systems outperform systems with receive-diversity-only when noise dominates. When co-channel interference from surrounding cells dominates, the differences shrink, as do the absolute numbers. We quantify these reductions for the specific cases studied, and discuss further areas of research.

Experimental investigation of correlation properties of MIMO radio channels for indoor picocell scenarios

Abstract: The present paper describes the set-up for the measurement of MIMO (multi-input-multi-output) radio channels as part of the European project METRA (Multi Element Transmit and Receive Antenna). Inputs for the stochastic model described by Pedersen, Andersen, Kermoal and Mogensen (see IEEE Vehicular Technology Conference VTC 2000 Fall, Boston, USA, 2000) are extracted from the measurement results and fed into a COSSAP(R) block implementing this model. A good matching between the eigenanalysis performed on both measured and simulated signals is shown.

Space-time processing for multiple-input, multiple-output, wireless systems

Abstract: In a MIMO system the signals transmitted from the various antennas are processed so as to improve the ability of the receiver to extract them from the received signal even in the face of some correlation. More specifically the number of bit streams that is transmitted simultaneously is adjusted, e.g., reduced, depending on the level of correlation, while multiple versions of each bit stream, variously weighted, are transmitted simultaneously. The variously weighted versions are combined to produced one combined weighted signal. The receiver processes the received signals in the same manner as it would have had all the signals reaching the receive antennas been uncorrelated. The weight vectors may be determined by the forward channel transmitter using the channel properties of the forward link which are made known to the transmitter of the forward link by being transmitted from the receiver of the forward link by the transmitter of the reverse link or the weight vectors may be determined by the forward channel transmitter using the channel properties of the forward link and the determined weight vectors are made known to the transmitter of the forward link by being transmitted from the receiver of the forward link by the transmitter of the reverse link. The channel properties used to determine the weight vectors may include the channel response from the transmitter to the receiver and the covariance matrix of noise and interference measured at the receiver.

Simulation results for an interference-limited multiple input multiple output cellular system

Abstract: We describe a simulation study of a cellular system using multiple-input multiple-output (MIMO) antenna techniques along with adaptive modulation and aggressive frequency reuse. We show, for the case of 3 transmit and 3 receive antennas, how much MIMO systems outperform systems with receive-diversity-only when noise dominates. When co-channel interference from surrounding cells dominates, the differences shrink, as do the absolute numbers. We quantify these reductions for the specific cases studied, and discuss further areas of research.

Near-optimal selection of transmit antennas for a MIMO channel based on Shannon capacity

Abstract: Current wireless MIMO (multiple transmit and receive antenna) systems are designed with the assumption that the fading channel is estimated perfectly at the receiver while the transmitter has no channel knowledge. If even a small amount of information is fed back to the transmitter, the capacity of the resulting channel increases appreciably. We consider a low-scattering, quasistatic environment where the matrix channel is rank deficient. Previous results (Gore et al. 2000, and Nabar et al. 2000) for such a channel indicate that channel capacity can be increased by a judicious choice of fewer transmit antennas. The optimal subset of transmit antennas is computed by the receiver as the subset that induces the highest Shannon capacity of all subsets of the same cardinality. Here we describe a computationally efficient, near-optimal search technique for the optimal subset based on classical waterpouring. We also provide enhanced search techniques based on partial waterpouring and uniform pourer allocation over the strongest channel modes that outperform waterpouring at high signal to noise ratios.

Improving BLAST performance using space-time block codes and turbo decoding

Abstract: An architecture that theoretically achieves channel capacity on multi-input multi-output channels was proposed by Foschini (1996) as BLAST. We show that in practical systems BLAST performance is limited by error propagation. The theoretically possible increase in diversity level during successive detection steps cannot be achieved. We evaluate the possibilities to improve BLAST performance. We first analyze an MMSE solution compared to zero forcing. Furthermore, we show the benefits of soft over hard interference cancellation and propose an iterative turbo detection algorithm. Finally, we apply transmit diversity with space-time block codes to BLAST. This improves the overall diversity level and reduces the number of required receive antennas.

State-space system identification-toward MIMO models for modal analysis and optimization of bulk power systems

Abstract: This paper provides an introduction to a reduced-order, small-signal identification approach to modal analysis and control of large power systems. Being based on system-wide responses to low-energy pulse excitations generated using conventional time-domain simulation software such as PSS/E or EMTSP, it readily takes full advantage of the large built-in model database. The proposed multi-input-multi-output (MIMO) minimal realization reveals naturally the dominant modes attached specifically to a given device, as well as the transfer functions relating selected measurement and observation sites. It plays a complementary role to direct computation of the full-scale linearized model using a comprehensive program such as MASS, after a summary of the theoretical work initiated at Hydro-Quebec in the early 1990s to promote this approach and put it into routine use, we present the main challenges in developing a production grade computer code. Detailed examples inspired by actual network studies at Hydro-Quebec are discussed, the most complex of them involving the identification of a 125th order MIMO model with 26 inputs and 26 outputs.

Multiple-input multiple-output (MIMO) radio channel measurements

Abstract: We present results from the first field test to characterize the mobile multiple-input multiple-output (MIMO) radio channel. We measured the capacity, normalized to a single antenna system, and fading correlation between antennas of a system with 4 antennas on a laptop computer and 4 antennas at a rooftop base station. The field test results show that close to the theoretical 4 times the capacity of a single antenna system can be supported in a 30 kHz channel with dual-polarized, spatially-separated base station and terminal antennas. For this 4/spl times/4 MIMO system the degradation in capacity due to fading correlation is small even with correlation coefficients as high as 0.5. Close to the theoretical 4 times capacity was achieved under a variety of test runs, including suburban drives, highway drives, and pedestrian routes, both close to the base station and inside a house a few miles from the base station. Therefore, these results show that it may be possible to provide in excess of 1 Mbps in a 200 kHz mobile radio channel (for the 3G wireless TDMA system EDGE) with the appropriate base station antennas.

Multiple-input multiple-output (MIMO) radio channel measurements

Abstract: Summary form only given. Multiple antennas at both the transmitter and receiver have the potential to significantly increase the capacity of a wireless communications channel. That is, using multiple-input (MIMO) techniques with these antennas, multiple independent channels can be supported in the same bandwidth, but only if the scattering environment is rich enough. Recent research has shown that high theoretical capacity is possible-data rates as high as 40 bits/s/Hz have been demonstrated (in an indoor slow fading environment). However, in cellular mobile radio, the channel differs in several important ways from the indoor channel. Therefore, to determine the potential of MIMO techniques for 3G and 4G wireless systems, we conducted the first field tests to characterize the mobile MIMO radio channel in a typical cellular environment. We present field test results showing the potential increase in capacity using 4 transmit and 4 receive antennas at both the base station and terminal in a mobile environment.

Downlink and uplink channel structures for downlink shared channel system

Abstract: An uplink and downlink channel structure supports a shared downlink data channel. The new structure accommodates advanced physical and Medium Access Control (MAC) layer techniques, such as incremental redundancy (IR), fast adaptation to channel conditions, and multiple input multiple output (MIMO) antenna configuration. The proposed changes are intended to lead to a downlink structure that achieves higher spectral efficiency for the packet oriented services over then shared downlink channel. Additionally, the new structure uses the base station transmit power information and of the channelization (OVSF) code space more efficiently.

Synchronization in a multiple-input/multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system for wireless applications

Abstract: Methods and apparatus are described for time synchronizing a receiver to orthogonal frequency division multiplexing (OFDM) signals in a multiple-input/multiple-output (MIMO) system, the signals being transmitted from multiple transmitters and received at multiple receivers. The method includes determining the frequency offset and the sampling clock offset of the received signals.

A multiple input-multiple output channel model for simulation of Tx- and Rx-diversity wireless systems

Abstract: Space-time receivers for wireless communication systems offer the possibility to have both Tx- and Rx-antennas. For a realistic simulation of such systems, a multiple input multiple output (MIMO) spatial channel model is required which reasonably characterizes the space- and time-variant effects of the mobile radio channel. This paper describes a space-time vector channel model with realistic fading simulation for different scenarios. Mutual correlation between the fading coefficients is considered. This allows an estimation of the diversity gain, that can be achieved with space-time receivers in different scenarios.

Direct blind MMSE channel equalization based on second-order statistics

Abstract: A family of new MMSE blind channel equalization algorithms based on second-order statistics are proposed. Instead of estimating the channel impulse response, we directly estimate the cross-correlation function needed in Wiener-Hopf filters. We develop several different schemes to estimate the cross-correlation vector, with which different Wiener filters are derived according to minimum mean square error (MMSE). Unlike many known sub-space methods, these equalization algorithms do not rely on signal and noise subspace separation and are consequently more robust to channel order estimation errors. Their implementation requires no adjustment for either single- or multiple-user systems. They can effectively equalize single-input multiple-output (SIMO) systems and can reduce the multiple-input multiple-output (MIMO) systems into a memoryless signal mixing system for source separation. The implementations of these algorithms on SIMO system are given, and simulation examples are provided to demonstrate their superior performance over some existing algorithms.

Multistep linear predictors-based blind identification and equalization of multiple-input multiple-output channels

Abstract: Channel estimation and blind equalization of multiple-input multiple-output (MIMO) communications channels is considered using primarily the second-order statistics of the data. Such models arise when single receiver data from multiple sources is fractionally sampled (assuming that there is excess bandwidth) or when an antenna array is used with or without fractional sampling. We consider the estimation of (partial) channel impulse response and design of finite-length minimum mean-square error (MMSE) blind equalizers. We extend the multistep linear prediction approach to MIMO channels where the multichannel transfer function need not be column reduced. Moreover, we allow infinite impulse response (IIR) channels as well as the case where the "subchannel" transfer functions have common zeros. In the past, this approach has been confined to SIMO finite impulse response (FIR) channels with no common subchannel zeros. A related existing approach applicable to MIMO channels is restricted to FIR column-reduced systems with equal length subchannels. In our approach, the knowledge of the nature of the underlying model (FIR or IIR) or the model order is not required. Our approach works when the "subchannel" transfer functions have common zeros, as long as the common zeros are minimum-phase zeros. The sources are recovered up to a unitary mixing matrix and are further "unmixed" using higher order statistics of the data. Illustrative computer simulation examples are provided.

On blind multiuser forward link channel estimation by the subspace method: identifiability results

Abstract: Blind channel estimation for periodic sequence DS-CDMA systems can be cast into the framework of "structured" blind estimation of multi-input/multi-output (MIMO) FIR systems, where the structure is imposed by the user's signatures. A possible approach to tackle this problem consists in looking for a structured solution to one of the blind MIMO-FIR systems, proposed previously. This is the approach undertaken by several authors. However, most of them did not address identifiability issues. In this paper, we first recall and reformulate some general MIMO FIR identification results of Meraim, Loubaton and Moulines (see IEEE Trans. Inform. Theory, vol.43, p.499-511, 1997), and point out some difficulties posed by the subspace approach. Next, we use the above material in order to analyze the behavior of the subspace forward link channel estimate of CDMA systems. We derive new results showing that the subspace method is not robust to an over-determination of the channel order greater than the spreading factor. If however the over-determination error is less than the spreading factor, we show that the subspace estimate is consistent if the codes of the users are properly designed.

Finite-length equalization over multi-input multi-output channels

Abstract: A MIMO Decision Feedback Equalizer improves operation of a receiver by cancelling the spatio-temporal interference effects caused by the MIMO channel memory with a set of FIR filters in both the feedforward and the feedback MIMO filters. The coefficients of these FIR filters can be fashioned to provide a variety of controls by the designer.

Feedforward plus feedback controller performance assessment of MIMO systems

Abstract: This paper is concerned with performance assessment of multiinput-multioutput (MIMO) feedforward plus feedback controllers. It is shown that the minimum feedforward plus feedback control variance can be estimated from routine operating data, and can then be used as a benchmark for performance assessment of feedforward and/or feedback controllers. The proposed method is illustrated by a numerical example and an industrial application.

MIMO channel capacity of a measured indoor radio channel at 5.8 GHz

Abstract: Multiple transmitters and receivers can be used to provide high link capacity in future wireless systems. Here, an analysis of indoor environment multiple-input-multiple-output measurements in the 5.8 GHz band is performed and the possible increase in capacity, utilizing multiple transmitters and receivers is examined. The investigation shows that in the measured indoor environment, the scattering is sufficiently rich to provide substantial link capacity increases. Furthermore, the effect of intra-element element spacing on, the channel capacity is studied. Finally the possible HiperLAN/2 MIMO channel capacity, based on the measurements, is examined.

A two-stage algorithm for MIMO blind deconvolution of nonstationary colored signals

Abstract: A new two-stage algorithm is proposed for the deconvolution of multi-input multi-output (MIMO) systems with colored input signals. While many blind deconvolution algorithms in the literature utilize high order statistics of the output signal for white input signals, the additional information contained in colored input signals allows the design of second-order statistical algorithms. In fact, practical signal sources such as speech signals do have distinct, nonstationary, colored power spectral densities. We present a two-stage signal separation approach in which the first step utilizes a matrix pencil between output auto-correlation matrices at different delays, whereas the second stage adopts a subspace method to identify and deconvolve MIMO systems.

Capacity variation of indoor multiple-input multiple-output channels

Abstract: Measurements of indoor multiple-input multiple-output (MIMO) channels have been conducted at 5.2 GHz and their information theoretic capacity analysed. It has been found that the variation of received signal-to-noise ratio has a greater influence on this capacity than the variation due to changes in the correlation of the channel response matrix.

On a whitening approach to partial channel estimation and blind equalization of FIR/IIR multiple-input multiple-output channels

Abstract: Channel estimation and blind equalization of multiple-input multiple-output (MIMO) communications channels is considered using primarily the second-order statistics of the data. Such models arise when a single receiver data from multiple sources is fractionally sampled (assuming that there is excess bandwidth) or when an antenna array is used with or without fractional sampling. We consider estimation of (partial) channel impulse response and design of finite-length minimum mean-square error (MMSE) blind equalizers. The basis of the approach is the design of a zero-forcing equalizer that whitens the noise-free data. We allow infinite impulse response (IIR) channels. Moreover, the multichannel transfer function need not be column reduced. Our approaches also work when the "subchannel" transfer functions have common zeros as long as the common zeros are minimum-phase zeros. The channel length or model orders need not be known. The sources are recovered up to a unitary mixing matrix and are further "unmixed" using higher order statistics of the data. A linear prediction approach is also considered under the above conditions of possibly IIR channels, common subchannel zeros/factors, and not-necessarily column reduced channels. Four illustrative simulation examples are provided.

MIMO environmental capacity sensitivity

Abstract: Wireless communications using multiple input multiple output (MIMO) systems enable increased spectral efficiency for a given total transmit power. The increased capacity is achieved through the introduction of additional spatial channels (space-time coding). In this paper, MIMO capacity is calculated as a function of environmental factors, including channel complexity, external interference and channel estimation error. The capacity of MIMO systems, where both the transmitter and receiver know the channel (channel estimate feedback), is compared with single input multiple output (SIMO) and MIMO systems, where only the receiver knows the channel. The channel complexity is studied using a simple statistical physical scattering model. Finally, an expression for capacity loss particular to channel estimation error at the transmitter is introduced.

Adaptive spatial-subcarrier trellis coded MQAM and power optimization for OFDM transmissions

Abstract: Space-time coding or coded modulation has demonstrated that significant increases in system capacity and performance can be achieved by incorporating multiple antennas at the transmitter and (optional) multiple antennas at the receiver. In this paper, we propose an adaptive spatial-subcarrier trellis coded modulation using MQAM for orthogonal frequency division multiplexing (OFDM) transmission by using instantaneous channel state information and employing multiple antennas at both the transmitter and the receiver. In particular, our objective is to minimize the total transmit power required for each OFDM transmission, by optimizing the power allocation, code rate and modulation scheme in each spatial-subcarrier channel, while maintaining a given data rate and bit error probability. To illustrate the potential of our proposed system, Monte Carlo simulation results are provided.

Adaptive equalization of multiple-input multiple-output (MIMO) channels

Abstract: The paper proposes and investigates a new approach to adaptive spatio-temporal equalization for MIMO (multiple-input multiple-output) channels. A system with n transmit and m (m/spl ges/n) receiver antennas is assumed. A decision feedback equalizer is considered. A least squares solution is first formulated, based on which a recursive solution using Riccati recursions is proposed. The proposed solution is tested by simulating the MIMO system. It is shown that the adaptive solution achieves the same performance as the optimum least squares solution. The effect of the nondiagonal channel elements (acting as interference) on the system performance is also studied. It has been shown that in order to achieve better performance, the interference from nondiagonal channel elements needs to be minimized. This can be done by using orthogonal transmission. Moreover the proposed solution do not require channel identification and will also enable equalizer adaptation to channel changes.

Modeling multipath fading channel dynamics for packet data performance analysis

Abstract: The multipath fading channel modeling traditionally focuses on physical level dynamics such as signal strength and bit error rate. In this paper we characterize multipath fading channel dynamics at the packet level and analyze the corresponding data queueing performance in various environments. The integration of wireless channel modeling and data queueing analysis provides us a unique way to capture important channel statistics with respect to various wireless network factors such as channel bandwidth, mobile speed and channel coding. The second order channel statistics, i.e. channel power spectrum, is found to play an important role in the modeling of multipath fading channels. The data queueing performance is largely dependent on the interaction between the channel power spectrum and the data arrival power spectrum; whichever has lower frequency power will have more impact on queueing performance. Note that the data arrival power spectrum provides a measure of burstiness and correlation behavior of data packet arrivals. Throughout the paper, we use the Markov chain modeling technique to match the measured important channel statistics for both channel modeling and queueing analysis.