Recursive spatial multiplexing in interference-limited indoor scenarios

Publication typeProceedings Article
Publication date2014-11-01
Abstract
Recursive spatial multiplexing (RSM), a closed loop multiple-input multiple-output (MIMO) structure for achieving the capacity offered by MIMO channels with a low-complexity detector, is investigated in measured indoor MIMO transmission channels limited by different types of interference. It is seen that RSM can deal effectively with interferences following either a Gaussian mixture or Middleton distribution. In cases of interferences which are symmetric alpha stable distributed, however, RSM suffers from a performance degradation. Performance improvements resulting from the use of a convolutional coding at the single-input single-output (SISO) encoder of the RSM architecture are investigated for the different interference distributions.
Mansour N., Dahlhaus D., Shah I., Hunziker T.
2014-06-01 citations by CoLab: 1 Abstract
A realistic Recursive Spatial Multiplexing (RSM) scheme for the case of a wireless feedback channel with limited capacity is considered where the identifier for the critical subspaces are encoded using either Grassmannian or vector quantizers. Optimum and suboptimum encoding schemes are proposed and analyzed. The threshold for the eigenvalues of the channel matrix required in the receiver for determining the critical subspaces is chosen based on optimizing channel capacity and uncoded biterror rates within the inner transceiver. It is shown that the limited feedback channel capacity limits the RSM performance, critically determines the achievable bit-error rates and defines the range of signal-to-noise ratio values where RSM outperforms open-loop multiple-input multiple-output transmission schemes.
Mohamad U.Y., Shah I.A., Hunziker T., Dahlhaus D.
2013-11-01 citations by CoLab: 1 Abstract
Recursive Spatial Multiplexing (RSM) is a closed loop multiple-input multiple-output (MIMO) structure for achieving the capacity offered by MIMO channels with a low-complexity detector. We investigate how to make RSM able to deal with different interference scenarios. The interference at the receiver side is considered as a vector-valued stochastic process characterized by a covariance matrix which is to be estimated and used subsequently for defining the retransmission subspace identifier to be fed back to the transmitter. We consider both the sample covariance matrix (SCM) estimator and an empirical Bayesian (EB) scheme as well as different probability distribution functions and correlation properties of the interference vectors. It turns out that the proposed RSM modification substantially improves the bit-error rate performance in the presence of interference where EB and SCM perform comparably due to the conditions for the covariance matrix estimation in RSM with limited frame length. Moreover, adaptive RSM leads to a performance being independent of the correlation coefficient of the interference vector.
Gulati K., Evans B.L., Andrews J.G., Tinsley K.R.
2010-12-01 citations by CoLab: 138 Abstract
With increasing spatial reuse of radio spectrum, co-channel interference is becoming a dominant noise source and may severely degrade the communication performance of wireless transceivers. In this paper, we consider the problem of statistical-physical modeling of co-channel interference from an annular field of Poisson or Poisson-Poisson cluster distributed interferers. Poisson and Poisson-Poisson cluster processes are commonly used to model interferer distributions in large wireless networks without and with interferer clustering, respectively. Further, by considering the interferers distributed over a parametric annular region, we derive interference statistics for finite- and infinite- area interference region with and without a guard zone around the receiver. Statistical modeling of interference is a useful tool to analyze outage probabilities in wireless networks and design interference-aware transceivers. Our contributions include: 1) developing a unified framework for deriving interference models for various wireless network environments; 2) demonstrating the applicability of the symmetric alpha stable and Gaussian mixture (with Middleton Class A as a particular form) distributions in modeling co-channel interference; and 3) deriving analytical conditions on the system model parameters for which these distributions accurately model the statistical properties of the interference. Applications include co-channel interference modeling for various wireless networks, including wireless ad hoc, cellular, local area, and femtocell networks.
Shah I.A., Hunziker T., Edlich T., Dahlhaus D.
2010-11-01 citations by CoLab: 3
Loyka S., Levin G.
2009-03-19 citations by CoLab: 39 Abstract
Various normalizations of the MIMO channel matrix are discussed from a physical perspective. It is demonstrated that the physics of antenna arrays and propagation channel should be taken into account when normalization is chosen, so that SNR has proper physical meaning, the conclusions are physical and correspond to realistic systems. The antenna array geometry and the transmission strategy (coherent/non-coherent) limits the choice of normalization and determines how the capacity and other performance metrics scale with the number of antennas, which is more pronounced for densely-populated antenna arrays. This is especially important for an asymptotic analysis, when the number of antennas increases to infinity. Limitations of such analysis from the physical perspective are pointed out.
Win M.Z., Pinto P.C., Shepp L.A.
2009-02-01 citations by CoLab: 508 Abstract
In this paper, we introduce a mathematical framework for the characterization of network interference in wireless systems. We consider a network in which the interferers are scattered according to a spatial Poisson process and are operating asynchronously in a wireless environment subject to path loss, shadowing, and multipath fading. We start by determining the statistical distribution of the aggregate network interference. We then investigate four applications of the proposed model: 1) interference in cognitive radio networks; 2) interference in wireless packet networks; 3) spectrum of the aggregate radio-frequency emission of wireless networks; and 4) coexistence between ultrawideband and narrowband systems. Our framework accounts for all the essential physical parameters that affect network interference, such as the wireless propagation effects, the transmission technology, the spatial density of interferers, and the transmitted power of the interferers.
Hunziker T., Edlich T., Dahlhaus D.
2007-01-01 citations by CoLab: 8
Lebrun G., Gao J., Faulkner M.
2005-03-01 citations by CoLab: 131 Abstract
The performance of a system using singular value decomposition (SVD) over a multiple-input multiple-output (MIMO) channel is dependent on the accuracy of the channel state information (CSI) at the transmitter and the receiver. In time division duplex (TDD) systems, the channel is reciprocal, hence the CSI can be retrieved through estimation of pilot symbols and applied to transmission. However, for a time-varying channel, the estimated CSI at the transmitter is incorrect due to an inherent delay between the estimation of the CSI and the transmission of data. A typical system employing SVD suffers degradation in capacity when incorrect CSI is used to transmit data. This paper proposes a new linear processing architecture, which reduces the effect of incorrect CSI at the transmitter. No additional pilot signals are required. It is shown at terminal velocity of 2 m.s/sup -1/ for the Hiperlan 2 standards, that the proposed architecture has a capacity of one bit lower than the theoretical channel capacity. At low velocities, this architecture outperforms (in terms of capacity) simpler systems that do not require CSI at the transmitter.
Loyka S., Gagnon F.
2004-07-13 citations by CoLab: 150 Abstract
A geometrically based analytical approach to the performance analysis of the V-BLAST algorithm is presented in this paper, which is based on the analytical model of the Gramm-Schmidt process. This approach presents a new geometrical view of the V-BLAST and explains some of its properties in a complete and rigorous form, including a statistical analysis of postprocessing signal-to-noise ratios for a 2/spl times/n system (where n is the number of receive antennas). Closed-form analytical expressions of the vector signal at ith processing step and its power are presented. A rigorous proof that the diversity order at ith step (without optimal ordering) is (n-m+i) is given (where m is the number of transmit antennas). It is shown that the optimal ordering is based on the least correlation criterion and that the after-processing signal power is determined by the channel correlation matrices in a fashion similar to the channel capacity. Closed-form analytical expressions are derived for outage probabilities and average BER of a 2/spl times/n system. The effect of the optimal ordering is shown to be to increase the first step SNR by 3 dB (rather than to increase the diversity order as one might intuitively expect based on the selection combining argument) and to increase the second step outage probability twice.
Middleton D.
1999-05-01 citations by CoLab: 533 Abstract
The subject here is generalized (i.e., non-Gaussian) noise models, and specifically their first-order probability density functions (PDFs). Attention is focused primarily on the author's canonical statistical-physical Class A and Class B models. In particular, Class A noise describes the type of electromagnetic interference (EMI) often encountered in telecommunication applications, where this ambient noise is largely due to other, intelligent telecommunication operations. On the other hand, ambient Class B noise usually represents man-made or natural nonintelligent-i.e., nonmessage-bearing noise-and is highly impulsive. Class A noise is not an /spl alpha/-stable process, nor is it reducible to such, except in the limiting Gaussian cases of high-density noise (by the central limit theorem). Class B noise is also asymptotically normal (before model approximation). Under rather broad conditions, principally governed by the source propagation and distribution scenarios, the PDF of Class B noise alone (no Gaussian component) can usually be approximated by (1) a symmetric Gaussian /spl alpha/-stable (S/spl alpha/S) model in the case of narrowband reception, or when the PDF /spl omega//sub 1/(/spl alpha/) of the amplitude is symmetric; and (2) a nonsymmetric /spl alpha/-stable (NS/spl alpha/S) model (no Gaussian component) can be constructed in broadband regimes. New results here include: (i) counting functional methods for constructing the general qth-order characteristic functions (CFs) of Class A and Class B noise, from which (all) moments and (in principle), the PDFs follow; (ii) the first-order CFs, PDFs, and cumulative probabilities (APDs) of nonsymmetric broadband Class B noise, extended to include additive Gauss noise (AGN); (iii) proof of the existence of all moments in the basic Class A and Class B models; (iv) the key physical role of AGN and the fact that AGN removes /spl alpha/-stability; (v) the explicit roles of the propagation and distribution scenarios; and (vi) extension to noise fields. Although telecommunication applications are emphasized, Class A and Class B noise models apply selectively, but equally well, to other physical regimes, e.g., underwater acoustics and EM (radar, optics, etc.). Supportive empirical data are included.
Mondal B., Heath R.W., Leif H.W.
citations by CoLab: 14
van de Beek J.-., Edfors O., Sandell M., Wilson S.K., Borjesson P.O.
citations by CoLab: 783

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