Multiple-input Multiple-output Channel Model Research Articles

Gigabit DSL

This paper applies multiple-input multiple-output (MIMO) transmission methods to multiwire communication systems. Using channel matrices generated from a binder MIMO channel model, a performance assessment of digital subscriber line (DSL) technology based on MIMO transmission methods finds that symmetric data rates of more than 1 Gbps are achievable over four twisted pairs (category 3) for a 300 m range. Similar results are also obtained for a ldquoquadrdquo cable. To achieve this data rate, this paper proposes that the source and load be excited using common mode.

An Extended One-Ring MIMO Channel Model

In this paper we develop a multiple input multiple output (MIMO) channel model and derive its spatial and temporal correlation properties. We present a generalized methodology to derive the spatial correlation when the angles of arrival (AoA) and angles of departure (AoD) are either independent or partly correlated. Our model therefore spans the full range from well-established single ring models, where AoA and AoD are fully correlated to complex industrial channel models where they are uncorrelated. It is shown that first order and second order approximations to the channel give rise to a single- Kroneckermodel and a sum-Kroneckermodel respectively. We compare our model to other MIMO channel models in terms of correlation structure and the ergodic mutual information (EMI) and study the effect of the non-Kronecker correlation structure.

Binder MIMO Channels

This paper introduces a multiple-input multiple-output channel model for the characterization of a binder of telephone lines. This model is based on multiconductor transmission line theory, and uses parameters that can be obtained from electromagnetic theory or measured data. The model generates frequency-dependent channel/binder transfer function matrices as a function of cable type, geometric line-spacing and twist-length parameters, and source--load configurations. The model allows the extraction of the magnitude and the phase of individual near end crosstalk, far end crosstalk, split-pair, and phantom transfer functions from the transfer function matrix of the binder. These individual crosstalk transfer functions are often found to be very sensitive to small imperfections in the binder. Examples of category 3 twisted pair American telephone lines and ldquoquadrdquo telephone cables are also presented.

Multi-Satellite MIMO Communications at Ku-Band and Above: Investigations on Spatial Multiplexing for Capacity Improvement and Selection Diversity for Interference Mitigation

This paper investigates the applicability of multiple-input multiple-output (MIMO) technology to satellite communications at the Ku-band and above. After introducing the possible diversity sources to form a MIMO matrix channel in a satellite environment, particular emphasis is put on satellite diversity. Two specific different topics from the field of MIMO technology applications to satellite communications at these frequencies are further analyzed: (i) capacity improvement achieved by MIMO spatial multiplexing systems and (ii) interference mitigation achieved by MIMO diversity systems employing receive antenna selection. In the first case, a single-user capacity analysis of a satellite MIMO spatial multiplexing system is presented and a useful analytical closed form expression is derived for the outage capacity achieved. In the second case, a satellite MIMO diversity system with receive antenna selection is considered, adjacent satellite cochannel interference on its forward link is studied and an analytical model predicting the interference mitigation achieved is presented. In both cases, an appropriate physical MIMO channel model is assumed which takes into account the propagation phenomena related to the frequencies of interest, such as clear line-of-sight operation, high antenna directivity, the effect of rain fading, and the slant path lengths difference. Useful numerical results obtained through the analytical expressions derived are presented to compare the performance of multi-satellite MIMO systems to relevant single-input single-output (SISO) ones.

Low Elevation Wideband Land Mobile Satellite MIMO Channel Characteristics

This paper presents wideband characteristics of a low elevation, land mobile, single satellite, dual circularly polarized, multiple-input multiple-output (MIMO) radio propagation channel. The work is based on S-band measurements using an artificial platform to represent the satellite, situated on a hilltop, to a mobile vehicle located in three environments: tree-lined road, suburban and urban. First and second order statistics and inter-tap cross-correlations are derived for both large and small scale fading, over the delay and combined spatial/polarization domains from the measured 2times2 MIMO matrix channel data. The work is aimed towards further development of a valid wideband land mobile satellite (LMS) MIMO channel model. Such systems may form the next generation of satellite delivered mobile broadband Internet services.

A DSFBC-OFDM for a Next Generation Broadcasting System With Multiple Antennas

In this paper, we propose a differential space-frequency block code-orthogonal frequency division multiplexing (DSFBC-OFDM) scheme as a multiple-input multiple-output (MIMO) transmission technique for next generation broadcasting system. A linear decoding method for DSFBC, which performs comparably to the ML decoding method, is derived for the cases of two or four transmit antennas. A simple table lookup method is proposed to improve the efficiency of the encoding/decoding process of DSFBC for the case of non-constant modulus constellations. This not only reduces the computational load, but also removes the necessity of channel estimation. Also, synchronization techniques with a DSFBC-encoded phase reference symbol (PRS) are discussed. Finally, an MIMO channel model for the next generation broadcasting system is developed by extending the 3GPP MIMO model to fit broadcasting environments. The MIMO channel model is then used to compare BER performances of differential space block code schemes for various channel environments. Simulation results show that the DSFBC-16QAM scheme using either four transmit antennas with one receive antenna or two transmit antennas with two receive antennas achieves a performance gain of 12 dB, with a data rate twice faster than that of the conventional DQPSK scheme

Bit Error Rate Minimizing Channel Shortening Equalizers for Cyclic Prefixed Systems

Cyclic prefixed communications, such as multicarrier communications, first became widely used in the context of digital subscriber lines (DSL). In DSL, bit loading is allowed at the transmitter, and the performance metric is the bit rate that can be provided without exceeding a given bit error rate (BER). Wireless cyclic prefixed systems are now becoming increasingly popular, and in such systems the appropriate performance metric is the BER for a given bit loading at the transmitter. Cyclic prefixed systems perform well in the presence of multipath, provided that the channel delay spread is shorter than the guard interval between transmitted blocks. If this condition is not met, a channel shortening equalizer can be used to shorten the channel to the desired length. Previous work on channel shortening has largely been in the context of DSL, thus it has focused on maximizing the bit rate. In this paper, we propose a channel shortener that attempts to directly minimize the BER for a multiple-input multiple-output channel model. We simulate the performance of the resulting channel shortener and compare it to existing designs and the matched filter bound

Spatial-Temporal Correlation Properties of the 3GPP Spatial Channel Model and the Kronecker MIMO Channel Model

The performance of multiple-input multiple-output (MIMO) systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. This paper investigates the spatial-temporal correlation characteristics of the spatial channel model (SCM) in the Third Generation Partnership Project (3GPP) and the Kronecker-based stochastic model (KBSM) at three levels, namely, the cluster level, link level, and system level. The KBSM has both the spatial separability and spatial-temporal separability at all the three levels. The spatial-temporal separability is observed for the SCM only at the system level, but not at the cluster and link levels. The SCM shows the spatial separability at the link and system levels, but not at the cluster level since its spatial correlation is related to the joint distribution of the angle of arrival (AoA) and angle of departure (AoD). The KBSM with the Gaussian-shaped power azimuth spectrum (PAS) is found to fit best the 3GPP SCM in terms of the spatial correlations. Despite its simplicity and analytical tractability, the KBSM is restricted to model only the average spatial-temporal behavior of MIMO channels. The SCM provides more insights of the variations of different MIMO channel realizations, but the implementation complexity is relatively high.

On the ensemble average capacity of multiple‐input multiple‐output channels in outdoor line‐of‐sight multipath urban environments

Many statistical multiple‐input multiple‐output (MIMO) channel models have been extensively developed over the past few years. However, to better understand and exploit such MIMO channels, there is a need for a MIMO channel model that has a basis in the physical propagation mechanisms. In this paper, a wideband semideterministic MIMO model is derived to quantify the mean capacity in an urban line‐of‐sight (LOS) microcell. Specifically, the model considers scattering from large‐scale discontinuities on building faces randomly distributed along a street canyon. Using geometrical optics and the uniform theory of diffraction, the spatial correlations between any two receiving signals are evaluated and are used to compute the upper bound of the average MIMO capacity.

Benefit of pattern diversity via two-element array of circular patch antennas in indoor clustered MIMO channels

In this paper, we analyze a multiple-input multiple-output (MIMO) array consisting of two circular microstrip antennas, designed to exploit pattern diversity. We analytically derive the spatial correlation coefficients of this array as a function of the mode excited, for realistic clustered MIMO channel models. We compare the performance of the circular patch array (CPA) against an array of two spaced dipoles. In particular, we compute a theoretical tradeoff to predict when the pattern diversity provided by the CPA is more effective than space diversity from the uniform linear array (ULA), based on the eigenvalues of the spatial correlation matrix. Through simulations, we show that CPAs yield better performance or satisfy more restrictive size constraints than ULAs in clustered MIMO channels, depending on the element spacing of the ULA. These results make the CPA an attractive solution for miniaturized MIMO arrays for portable devices or access points.

MIMO systems for broadband wireless communications

The emergence of broadband wireless access (BWA) and mobility poses significant challenges to the future telecommunications landscape. Multiple input multiple output (MIMO) is a potential technology that can be used to improve system performances such as coverage, capacity and data rates for broadband wireless networks. Although this technology has proved to be beneficial for both current and future services by many research results, it is not clear how these benefits can be practically achieved with a MIMO system. Fundamental issues on capacity enhancement and performance limits need to be addressed before operators will be willing to deploy MIMO systems in their networks. This paper addresses some of the key issues that remain open regarding MIMO technology for BWA. The paper focuses on MIMO channel modelling and capacity analysis.

A stochastic MIMO channel model with joint correlation of both link ends

Abstract-This paper presents a novel stochastic channel model for multiple-input multiple-output (MIMO) wireless radio channels. In contrast to state-of-the-art stochastic MIMO channel models, the spatial correlation properties of the channel are not divided into separate contributions from transmitter and receiver. Instead, the joint correlation properties are modeled by describing the average coupling between the eigenmodes of the two link ends. The necessary and sufficient condition for the proposed model to hold is that the eigenbasis at the receiver is independent of the transmit weights, and vice versa. The authors discuss the mathematical elements of the model, which can be easily extracted from measurements, from a radio propagation point of view and explain the underlying assumption of the model in physical terms. The validation of the proposed model by means of measured data obtained from two completely different measurement campaigns reveals its ability to better predict capacity and spatial channel structure than other popular stochastic channel models.

Impact of Clustering in Indoor MIMO Propagation Using a Hybrid Channel Model

The clustering of propagating signals in indoor environments can influence the performance of multiple-input multiple-output (MIMO) systems that employ multiple-element antennas at the transmitter and receiver. In order to clarify the effect of clustering propagation on the performance of indoor MIMO systems, we propose a simple and efficient indoor MIMO channel model. The proposed model, which is validated with on-site measurements, combines the statistical characteristics of signal clusters with deterministic ray tracing approach. Using the proposed model, the effect of signal clusters and the presence of the line-of-sight component in indoor Ricean channels are studied. Simulation results on channel efficiency and the angular sensitivity for different antenna array topologies inside a specified indoor scenario are also provided. Our investigations confirm that the clustering of signals significantly affects the spatial correlation, and hence, the achievable indoor MIMO capacity.

MIMO Channel Modeling and the Principle of Maximum Entropy

We devise theoretical grounds for constructing channel models for multiple-input multiple-output (MIMO) systems based on information-theoretic tools. The paper provides a general method to derive a channel model which is consistent with one's state of knowledge. The framework we give here has already been fruitfully explored with success in the context of Bayesian spectrum analysis and parameter estimation. For each channel model, we conduct an asymptotic analysis (in the number of antennas) of the achievable transmission rate using tools from random matrix theory. A central limit theorem is provided on the asymptotic behavior of the mutual information and validated in the finite case by simulations. The results are useful both in terms of designing a system based on criteria such as quality of service and in optimizing transmissions in multiuser networks.

Optimizing the Joint Transmit and Receive MMSE Design Using Mode Selection

To approach the potential multiple-input multiple-output (MIMO) capacity while optimizing the system bit-error rate (BER) performance, the joint transmit and receive minimum mean squared error (joint Tx/Rx MMSE) design has been proposed. It is the optimal linear scheme for spatial multiplexing MIMO systems, assuming a fixed number of spatial streams p as well as fixed modulation and coding across these spatial streams. However, the number of spatial streams has been arbitrarily chosen and fixed, which may lead to an inefficient power allocation strategy and a poor BER performance. In this paper, we relax the constraint of fixed number of streams p and optimize this value for the current channel realization, under the constraints of fixed total transmit power P/sub T/ and fixed rate R, what we refer to as mode selection . Based on the observation of the existence of a dominant optimal number of streams value for the considered Rayleigh flat-fading MIMO channel model, we further propose an average mode selection that avoids the per-channel adaptation through using the latter dominant value for all channel realizations. Finally, we exhibit the significant BER improvement provided by our mode selection over the conventional joint Tx/Rx MMSE design. Such significant improvement is due to the better exploitation of the MIMO spatial diversity and the more efficient power allocation enabled by our mode selection.

Special Issue: Multiple‐Input Multiple‐Output (MIMO) Communications

The idea of using multiple transmit and receive antennas in wireless communication systems is one of the most important breakthroughs in communication theory during the last decade. Popularly referred to as MIMO technology, this concept can greatly improve data throughput and link performance in wireless networks. In principle, a MIMO system can operate in, or anywhere between, one of the two possible modes. If the transmitter knows the channel, then one can use spatial beamforming techniques to steer RF energy in the direction of the receiver. On the other hand, if the transmitter does not know the channel, one can use space-time coding which effectively distributes the transmitted power uniformly in all directions, and in addition augments the data with structure that can be used to combat from fading dips. Sometimes, space-time coding methods are grouped into two categories: those that focus on throughput improvement (e.g. Bell-Labs layered space-time architecture, BLAST), and those that solely aim at improving link performance (including, most notably, orthogonal block coding and transmit diversity schemes); however, this classification is simplistic and many of the currently best known schemes do not fall under any of these two groups. Space-time coding, beamforming and their various combinations are becoming relatively well understood in the research community—as evidenced by the literal explosion of research papers and books (e.g. [1,2]) on the topic. Nevertheless, researchers are continuing to explore the more intricate aspects of combined coding over space and time. The goal of this special issue has been to collect a few edge-cutting, high-quality papers that not only capture the state-ofthe-art of the field but also highlight open problems and current research topics. We are delighted to present eight papers that survived a very competitive peer review process. Broadly speaking, the papers can be grouped into four categories: two papers that deal with coding for MIMO, two papers on MIMO channel modeling and simulation, two papers on signal processing for MIMO and finally two papers on crosslayer design for MIMO systems. The first paper, ‘Iterative receivers for coded MIMO signaling’, by Biglieri, Nordio and Taricco, is a tutorial on iterative (turbo) processing for systems that concatenate a GF(2) channel code with a complex-valued multidimensional (matrix) channel. The authors present the topic using a first-principle approach, and they also describe how iterative coding and demodulation for MIMO models work and how they can be analyzed by using EXIT charts, a powerful technique so far mostly used for ‘classical’ turbo coding. The next paper, ‘Improving the performance of coded FDFR multi-antenna systems with turbo-decoding’, by Wang, Ma and Giannakis, continues on the theme of iterative receiver structures. In this work, the authors show how full-rate full-diversity (FDFR) space-time block codes, developed by the authors in their previous work, can be efficiently combined with GF(2) channel coding. This paper provides valuable insight into the trade-off between performance and complexity involved in the choice of linear space-time block codes versus using powerful GF(2) codes and their combination. The third paper, by Patzold and Hogstad, ‘A spacetime channel simulator for MIMO channel based on the geometrical one-ring scattering model’ describes a narrowband MIMO channel simulator based on a geometric model, and evaluates its accuracy. This topic is certainly important, as MIMO channels in reality often have different characteristics than toy models used in purely theoretical studies. The fourth paper, ‘Performance of MIMO spatial multiplexing algorithms using indoor channel measurements and models’, is also on performance evaluation of MIMO systems in realistic environments. The authors,

Multiple-Input Multiple-Output Fixed Wireless Radio Channel Measurements and Modeling Using Dual-Polarized Antennas at 2.5 GHz

This paper presents outdoor propagation measurements together with derivative analysis, modeling, and simulation of the 2/spl times/2 fixed wireless multiple-input multiple-output (MIMO) channel. Experimental data were collected in the suburban residential areas of San Jose, CA, at 2.48 GHz by using dual-polarized antennas. Measurement results include the estimation of path loss, Rician K-factor, cross-polarization discrimination (CPD), correlation coefficients, and the MIMO channel capacity. An elaborate K-factor model that assumes variation over location, time, and frequency is developed. Distance-dependent CPD models of the variable and constant signal components are proposed. A generalized 2/spl times/2 MIMO channel model is then derived based on the correlation among the path loss, the copolarized K-factor, and the CPD's distribution of the constant and scattered signal components. Finally, the MIMO channel response is simulated using the newly developed model, and results are found to be well in agreement with measurements.

A Discrete-Time Model for Triply Selective MIMO Rayleigh Fading Channels

A statistical discrete-time model is proposed for simulating wideband multiple-input multiple-output (MIMO) fading channels which are triply selective due to angle spread, Doppler spread, and delay spread. The new discrete-time MIMO channel model includes the combined effects of the transmit filter, physical MIMO multipath channel fading, and receive filter, and it has the same sampling period as that of the MIMO receiver. This leads to very efficient simulation of physical continuous-time MIMO channels. A new method is also presented to efficiently generate the MIMO channel stochastic coefficients. The statistical accuracy of the discrete-time MIMO channel model is rigorously verified through theoretical analysis and extensive simulations in different conditions. The high computational efficiency of the discrete-time MIMO channel model is illustrated by comparing it to that of the continuous-time MIMO channel model. The new model is further employed to evaluate the channel capacity of MIMO systems in a triply selective Rayleigh fading environment. The simulation results reveal some interesting effects of spatial correlations, multipaths, and number of antennas on the MIMO channel capacity.

Spatial multiplexing in correlated fading via the virtual channel representation

Spatial multiplexing techniques send independent data streams on different transmit antennas to maximally exploit the capacity of multiple-input multiple-output (MIMO) fading channels. Most existing multiplexing techniques are based on an idealized MIMO channel model representing a rich scattering environment. Realistic channels corresponding to scattering clusters exhibit correlated fading and can significantly compromise the performance of such techniques. In this paper, we study the design and performance of spatial multiplexing techniques based on a virtual representation of realistic MIMO fading channels. Since the nonvanishing elements of the virtual channel matrix are uncorrelated, they capture the essential degrees of freedom in the channel and provide a simple characterization of channel statistics. In particular, the pairwise-error probability (PEP) analysis for correlated channels is greatly simplified in the virtual representation. Using the PEP analysis, various precoding schemes are introduced to improve performance in virtual channels. Unitary precoding is proposed to provide robustness to unknown channel statistics. Nonunitary precoding techniques are proposed to exploit channel structure when channel statistics are known at the transmitter. Numerical results are presented to illustrate the attractive performance of the precoding techniques.

Models for MIMO propagation channels: a review

AbstractThis paper reviews recently published results on multiple input multiple output (MIMO) channel modeling. Both narrowband and wideband models are considered. We distinguish between two main approaches to MIMO channel modeling, that is, physically based and nonphysically based modeling. The nonphysical models primarily rely on the statistical characteristics of the MIMO channels obtained from the measured data, while the physical models describe the MIMO channel (or its distribution) via some physical parameters. We briefly review different MIMO channel models and discuss their relationships. Some interesting aspects will be described in more detail and we note areas in which few results are available. Copyright © 2002 John Wiley & Sons, Ltd.