Wideband Polarimetric Directional Propagation Channel Analysis Inside an Arched Tunnel

A wideband directional measurement campaign was managed inside an arched highway tunnel to analyze the radio propagation channel inside such tunnel for future cellular systems in terms of coverage, delay spread and dominant scatterers. Measurements were performed in 3 rounds with different transmitter positions. Using a wideband channel sounder equipped with a cylindrical dual polarized array at the receiver, the spatio-temporal characteristics of the received propagation paths could be estimated by means of a super-resolution estimation algorithm. The extracted paths using this super-resolution algorithm constitute 88% of the total received power. It was also observed that the line-of-sight component (53%) plus single-bounce scattering (26%) comprise up to 79% of the total received power. In other words, more than 90% (i.e. 79% in 88%) of the extracted paths consists of the line-of-sight component and single-bounce scatterings. The strong contribution from single-bounce scattering paths causes the path gain exponent along the tunnel to be larger than -2 which is the value for free space. This validates that there is wave guiding effect in the tunnel and coverage is extended relative to open space. The rms delay spreads are generally less than 20 ns and increase when influenced by scattering objects such as jetfans. The dominant scatterers are identified and classified into 6 classes based on the structure of the tunnel and existing objects such as ground, wall, light-frame, ceiling, jetfan and cleaner-parking. It was observed that scattering from ground was dominant among all classified scatterers in all scenarios.     

Joint Angular- and Delay-Domain MIMO Propagation Parameter Estimation Using Approximate ML Method

In this paper, we derive an estimation method that jointly estimates the parameters of the concentrated propagation paths and the distributed scattering component that are frequently observed in multiple-input multiple-output (MIMO) channel sounding measurements. The joint angular-delay domain model leads to a correlation matrix with high dimensionality, which makes direct implementation of a maximum-likelihood (ML) estimator unfeasible. We derive low-complexity methods for computing approximate ML estimates that exploit the structure of the covariance matrices. We propose an iterative two-step procedure that alternates between the estimation of the parameters of the concentrated propagation paths and the parameters of the distributed scattering. For the distributed scattering, the estimator first optimizes the parameters describing their time-delay structure. Then, using the estimated time-delay parameters, the parameters of the angular distributions are optimized. We present simulation results and compare the estimated time-delay and angular distributions to the actual distributions, demonstrating that high-quality estimates are obtained. The large sample performance of the estimator is studied by establishing the Cramer-Rao lower bound (CRLB) and comparing it to the variances of the estimates. The simulations show that the variance of the proposed estimation technique reaches the CRLB for relatively small sample size for most parameters, and no bias is observed.     

一种新的基于参数信道模型的MIMO信道估计算法

针对频率选择性块衰落MIMO信道,该文提出一种改进的基于参数信道模型的信道估计方法。该方法首先通过修正后的TST-MUSIC算法估计多径的传播时延和角度。由时延和角度信息,得到一种基于参数信道模型的信道估计方法。仿真结果表明此种方法可以有效地减少参数估计的维数,其性能要远远优于非参数的最小二乘估计器。     

Improving clustering performance using multipath component distance

The problem of identifying clusters from MIMO measurement data is addressed. Conventionally, visual inspection has been used for cluster identification, but this approach is impractical for a large amount of measurement data. For automatic clustering, the multipath component distance (MCD) is used to calculate the distance between individual multipath components estimated by a channel parameter estimator, such as SAGE. This distance is implemented in the well-known KMeans clustering algorithm. To demonstrate the effectiveness of the choice made, the performance of the MCD and the Euclidean distance were compared by clustering synthetic data generated by the 3GPP spatial channel model (SCM). Using the MCD significantly improved clustering performance     

Introducing Space into MIMO Capacity Calculations

The large spectral efficiencies promised for multiple-input multiple-output (MIMO) wireless fading channels are derived under certain conditions which do not fully take into account the spatial aspects of the channel. Spatial correlation, due to limited angular spread or insufficient antenna spacing, significantly reduces the performance of MIMO systems. In this paper we explore the effects of spatially selective channels on the capacity of MIMO systems via a new capacity expression which is more general and realistic than previous expressions. By including spatial information we derive a closed-form expression for ergodic capacity which uses the physics of signal propagation combined with the statistics of the scattering environment. This expression gives the capacity of a MIMO system in terms of antenna placement and scattering environment and leads to valuable insights into the factors determining capacity for a wide range of scattering models.     

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.     

Estimation of continuous flat fading MIMO channels

Multiple-input-multiple-output (MIMO) systems can provide high data rate wireless services in a rich scattering environment. We study one of the proposals for MIMO systems, the Bell Labs Layered Space-Time (BLAST) architecture. Channel estimation using training sequences is required for coherent detection in BLAST. We apply the maximum-likelihood channel estimator and the optimal training sequences for block flat fading channels to continuous flat fading channels and analyze the estimation error. The optimal training length and training interval that maximize the throughput for a given target bit error-rate are found by computer simulations as functions of the Doppler frequency and the number of antennas.     

Cluster Properties Investigated From a Series of Ultrawideband Double Directional Propagation Measurements in Home Environments

Results from double directional ultrawideband (UWB) channel sounding in a wooden house are described. The double directional channel sounder estimates directional information at both ends of the link, so that we can separate antenna directivity from the channel sounding results. We investigated the dominant propagation mechanisms by introducing cluster analyses. The detected propagation paths from the channel sounding were first classified into clusters in the angular-delay domain, and then properties of the clusters such as standard deviation of path positions, dynamic range of path power, and power distribution of clusters were derived. From the results, we discussed the similarities and differences between the measurement environment and the physical propagation phenomena. Finally, different types of scattering losses of the propagation paths were derived and modeled. The results from sounding and analysis contribute in the development of UWB propagation models and can be used in UWB propagation simulations     

Spatial precoder design for space–time coded MIMO systems: based on fixed parameters of MIMO channels

In realistic channel environments the performance of space–time coded multiple-input multiple output (MIMO) systems is significantly reduced due to non-ideal antenna placement and non-isotropic scattering. In this paper, by exploiting the spatial dimension of a MIMO channel we introduce the novel idea of linear spatial precoding (or power-loading) based on fixed and known parameters of MIMO channels to ameliorate the effects of non-ideal antenna placement on the performance of coherent (channel is known at the receiver) and non-coherent (channel is un-known at the receiver) space–time codes. Antenna spacing and antenna placement (geometry) are considered as fixed parameters of MIMO channels, which are readily known at the transmitter. With this design, the precoder is fixed for fixed antenna placement and the transmitter does not require any feedback of channel state information (partial or full) from the receiver. We also derive precoding schemes to exploit non-isotropic scattering distribution parameters of the scattering channel to improve the performance of space–time codes applied on MIMO systems. However, these schemes require the receiver to estimate the non-isotropic parameters and feed them back to the transmitter. Closed form solutions for precoding schemes are presented for systems with up to three receive antennas. A generalized method is proposed for more than three receive antennas.     

Joint decorrelating multiuser detection and channel estimation inasynchronous CDMA mobile communications channels

The asymptotic efficiencies of two decorrelators, path-by-path and channel-matched decorrelators, are analyzed in fading multipath propagation environments, and based upon the analytical results, a new joint multiuser detection and channel estimation scheme is proposed for asynchronous code division multiple access (CDMA) mobile communications channels. In the path-by-path decorrelator, each of the received signals corresponding to one of the multiple propagation paths is regarded as an independent interference source. On the contrary, in the channel-matched decorrelator, each composite signal transmitted from an identical user is regarded as a response of the multipath channel to the corresponding user's spreading sequence. The asymptotic efficiency of the path-by-path decorrelator is shown to drop rapidly as the number of simultaneous users increases. It is shown that the asymptotic efficiency can be made independent of the number of the propagation paths by the channel-matched decorrelator at the expense of requiring knowledge about the fading complex envelopes of all the propagation paths. The proposed joint multiuser detection and channel estimation scheme uses both path-by-path and channel-matched decorrelators. The path-by-path decorrelator is used for providing the channel estimator with the (noisy) channel information path-by-path, and decisions are made on the output of the channel-matched decorrelator. The decision results are fed back to the channel estimator, and used as the reference signals. The received complex envelope of each of the propagation paths is estimated in the channel estimator. Results of a series of exhaustive computer simulations are presented in order to demonstrate the overall performance of the proposed scheme, both in non-fading and fading multipath propagation environments     

The double-directional radio channel

We introduce the concept of the double-directional mobile radio channel. It is called this because it includes angular information at both link ends, e.g., at the base station and at the mobile station. We show that this angular information can be obtained with synchronized antenna arrays at both link ends. In wideband high-resolution measurements, we use a switched linear array at the receiver and a virtual-cross array at the transmitter. We evaluate the raw measurement data with a technique that alternately used estimation and beamforming, and that relied on ESPRIT (estimation of signal parameters via rotational invariance techniques) to obtain superresolution in both angular domains and in the delay domain. In sample microcellular scenarios (open and closed courtyard, line-of-sight and obstructed line-of-sight), up to 50 individual propagation paths are determined. The major multipath components are matched precisely to the physical environment by geometrical considerations. Up to three reflection/scattering points per propagation path are identified and localized, lending insight into the multipath spreading properties in a microcell. The extracted multipath parameters allow unambiguous scatterer identification and channel characterization, independently of a specific antenna, its configuration (single/array), and its pattern. The measurement results demonstrate a considerable amount of power being carried via multiply reflected components, thus suggesting revisiting the popular single-bounce propagation models. It turns out that the wideband double-directional evaluation is a most complete method for separating multipath components. Due to its excellent spatial resolution, the double-directional concept provides accurate estimates of the channel's multipath-richness, which is the important parameter for the capacity of multiple-input multiple-output (MIMO) channels     

Capacity scaling and spectral efficiency in wide-band correlated MIMO channels

The dramatic linear increase in ergodic capacity with the number of antennas promised by multiple-input multiple-output (MIMO) wireless communication systems is based on idealized channel models representing a rich scattering environment. Is such scaling sustainable in realistic scattering scenarios? Existing physical models, although realistic, are intractable for addressing this problem analytically due to their complicated nonlinear dependence on propagation path parameters, such as the angles of arrival and delays. In this paper, we leverage a recently introduced virtual representation of physical models that is essentially a Fourier series representation of wide-band MIMO channels in terms of fixed virtual angles and delays. Motivated by physical considerations, we propose a D-connected model for correlated channels defined by a virtual spatial channel matrix consisting of D nonvanishing diagonals with independent and identically distributed (i.i.d.) Gaussian entries. The parameter D provides a meaningful and tractable measure of the richness of scattering. We derive general bounds for the coherent ergodic capacity and investigate capacity scaling with the number of antennas and bandwidth. In the large antenna regime, we show that linear capacity scaling is possible if D scales linearly with the number of antennas. This, in turn, is possible if the number of resolvable paths grows quadratically with the number of antennas. The capacity saturates for linear growth in the number of paths (fixed D). The ergodic capacity does not depend on frequency selectivity of the channel in the wide-band case. Increasing bandwidth tightens the bounds and hastens the convergence of scaling behavior. For large bandwidth, the capacity scales linearly with the signal-to-noise ratio (SNR) as well. We also provide an explicit characterization of the wide-band slope recently proposed by Verdu. Numerical results are presented to illustrate the key theoretical results.     

Directional Estimation of Block-Fading MIMO Channels Using Spherical Harmonics Expansion and Tensor Analysis

The well-known benefits of multiple input multiple output (MIMO) wireless communication systems suppose an efficient use of spatial diversity at both the transmitter and receiver. An important and not well-explored path toward improving MIMO system performance using spatial diversity takes into account the interactions among the antennas and the (physical) propagation medium. In this work, spherical harmonics and tensor analysis are originally combined into the problem of MIMO channel modeling and estimation. The use of spherical harmonics allows to represent the antenna radiation patterns in terms of coefficients of an expansion of spatially orthogonal functions, thus decoupling the transmit and receive antenna array responses from the physical propagation medium. Assuming a single-scattering propagation scenario driven by a finite number of specular multipaths, the parallel factor model is used to decompose the spherical modes of the MIMO channel into a sum of rank-one spherical mode tensors, whose dimensions are transmit modes, receive modes, and time. Then, we extend the tensor modeling framework to double scattering channels by resorting to the PARATUCK model that captures the interactions between multiple-scattering clusters. Capitalizing on the structure of these tensor models, we derive tensor-based alternating least squares algorithms for estimating directional MIMO channels in the spherical harmonics domain, from which the directions of arrival and directions of departure are extracted by means of a MUSIC-based method. Simulation results are provided to assess the performance of the proposed algorithms in selected system configurations. Our results also show the impact of the spherical expansion order on the accuracy of DoD/DoA estimates using the proposed algorithms.     

Algorithms for the MIMO Single Relay Channel

The MIMO single relay channel consists of a transmitter, a relay, and a receiver, all equipped with multiple antennas, located in an environment with distance-dependent path loss as well as scattering. We describe an optimal and a heuristic algorithm to solve the spatial energy allocation problem for the MIMO single relay channel when the scattering clusters on the direct and relay links are non-overlapping. These algorithms can be applied to existing wireless LAN systems that aim to increase their performance via relays. By simulations, we compare the performances of joint and uniform energy allocations across the spatial channels, and the performances of a direct transmission system and a system that utilizes the relay node     

Capacity of multiple-antenna fading channels: spatial fading correlation, double scattering, and keyhole

The capacity of multiple-input multiple-output (MIMO) wireless channels is limited by both the spatial fading correlation and rank deficiency of the channel. While spatial fading correlation reduces the diversity gains, rank deficiency due to double scattering or keyhole effects decreases the spatial multiplexing gains of multiple-antenna channels. In this paper, taking into account realistic propagation environments in the presence of spatial fading correlation, double scattering, and keyhole effects, we analyze the ergodic (or mean) MIMO capacity for an arbitrary finite number of transmit and receive antennas. We assume that the channel is unknown at the transmitter and perfectly known at the receiver so that equal power is allocated to each of the transmit antennas. Using some statistical properties of complex random matrices such as Gaussian matrices, Wishart (1928) matrices, and quadratic forms in the Gaussian matrix, we present a closed-form expression for the ergodic capacity of independent Rayleigh-fading MIMO channels and a tight upper bound for spatially correlated/double scattering MIMO channels. We also derive a closed-form capacity formula for keyhole MIMO channels. This analytic formula explicitly shows that the use of multiple antennas in keyhole channels only offers the diversity advantage, but provides no spatial multiplexing gains. Numerical results demonstrate the accuracy of our analytical expressions and the tightness of upper bounds.     

Closed-form blind channel identification and source separation inSDMA systems through correlative coding

We address the problem of blind identification of multiuser multiple-input multiple-output (MIMO) finite-impulse response (FIR) digital systems. This problem arises in spatial division multiple access (SDMA) architectures for wireless communications. We present a closed-form, i.e., noniterative, consistent estimator for the MIMO channel based only on second-order statistics. To obtain this closed form we introduce spectral/correlation asymmetry between the sources by filtering each source output with adequate correlative filters. Our algorithm uses the closed form MIMO channel estimate to cancel the intersymbol interference (ISI) due to multipath propagation and to discriminate between the sources at the wireless base station receiver. Simulation results show that, for single-user channels, this technique yields better channel estimates in terms of mean-square error (MSE) and better probability of error than a well-known alternative method. Finally, we illustrate its performance for MIMO channels in the context of the global system for mobile communications (GSM) system     

Detection and Tracking of MIMO Propagation Path Parameters Using State-Space Approach

This paper describes a novel approach for detection, estimation and tracking of multiple-input multiple-output (MIMO) radio propagation parameters from multidimensional channel sounding measurements. A realistic state-space model is developed for the purpose, and the extended Kalman filter (EKF) is applied in a particular computationally efficient form to track the geometrical double-directional propagation path parameters. The observation model utilizes the dense multipath component (DMC), describing the distributed scattering in the channel, as part of the underlying noise process. The DMC model assumes an exponential profile in delay, and allows for an arbitrary angular distribution. In addition, a novel dynamic state dimension estimator using statistical goodness-of-fit tests is introduced. The employed methods are supported by illustrative estimation examples from MIMO channel sounding measurements.      

Stochastic Maximum-Likelihood Method for MIMO Propagation Parameter Estimation

In this paper, we derive a stochastic maximum-likelihood (ML) method for estimating spatio-temporal parameters for multiple-input multiple-output (MIMO) channels. Such estimators are needed in propagation studies where extensive channel measurements and sounding are required. These are seminal tasks in the process of developing advanced channel models. The proposed method employs an angular von Mises distribution model which is appropriate for angular data observed in channel measurement campaigns. The signal model is stochastic, and consequentially the method is particularly useful for estimation of the diffuse scattering component. This approach leads to lower complexity and faster convergence in comparison to deterministic models. These benefits are due to lower dimensionality of the model, leading to a simpler optimization problem. The statistical performance of the estimator is studied by establishing the Crameacuter-Rao lower bound (CRLB) and comparing the variances. The simulations show that the variance of the proposed estimation technique reaches the CRLB for relatively small sample size. The estimator is robust in the sense that meaningful results are obtained when applied to data generated by channel models other than the one used in its derivation     

Frequency-selective multiple-input multiple-output channel estimation with transmitter non-linearities

The authors propose an algorithm based on the knowledge of training sequences to obtain an asymptotically unbiased estimator of non-linear multiple-input multiple-output (MIMO) channels, which involves the radio frequency front-end non-linearity and linear frequency selective MIMO channels. Although the impact of non-linearity in the transmitter side has been widely studied, most work on the channel estimation assumes linear channel models and ignores the non-linear effects. In this study, we develop a nonlinear channel estimator that can simultaneously estimate the linear MIMO channel model and non-linearity of the transmitter is developed. With these two sets of parameters, the non-linear channel model can be fully described. This channel estimation algorithm is implemented over an empirical MIMO channel model using an orthogonal frequency division multiplexing system.