186 research outputs found
Spatial Precoder Design for Space-Time Coded MIMO Systems: Based on Fixed Parameters of MIMO Channels
In this paper, we introduce the novel use of linear spatial precoding based
on fixed and known parameters of multiple-input multiple-output (MIMO) channels
to improve the performance of space-time coded MIMO systems. We derive linear
spatial precoding schemes for both coherent (channel is known at the receiver)
and non-coherent (channel is un-known at the receiver) space-time coded MIMO
systems. Antenna spacing and antenna placement (geometry) are considered as
fixed parameters of MIMO channels, which are readily known at the transmitter.
These precoding schemes exploit the antenna placement information at both ends
of the MIMO channel to ameliorate the effect of non-ideal antenna placement on
the performance of space-time coded systems. In these schemes, the precoder is
fixed for given transmit and receive antenna configurations and transmitter
does not require any feedback of channel state information (partial or full)
from the receiver. Closed form solutions for both precoding schemes are
presented for systems with up to three receiver antennas. A generalized method
is proposed for more than three receiver antennas. We use the coherent
space-time block codes (STBC) and differential space-time block codes to
analyze the performance of proposed precoding schemes. Simulation results show
that at low SNRs, both precoders give significant performance improvement over
a non-precoded system for small antenna aperture sizes.Comment: 15 Figures, 1-Table. Submitted to Personal Wireless Communications
Springer 08/12/200
A Survey on MIMO Transmission with Discrete Input Signals: Technical Challenges, Advances, and Future Trends
Multiple antennas have been exploited for spatial multiplexing and diversity
transmission in a wide range of communication applications. However, most of
the advances in the design of high speed wireless multiple-input multiple
output (MIMO) systems are based on information-theoretic principles that
demonstrate how to efficiently transmit signals conforming to Gaussian
distribution. Although the Gaussian signal is capacity-achieving, signals
conforming to discrete constellations are transmitted in practical
communication systems. As a result, this paper is motivated to provide a
comprehensive overview on MIMO transmission design with discrete input signals.
We first summarize the existing fundamental results for MIMO systems with
discrete input signals. Then, focusing on the basic point-to-point MIMO
systems, we examine transmission schemes based on three most important criteria
for communication systems: the mutual information driven designs, the mean
square error driven designs, and the diversity driven designs. Particularly, a
unified framework which designs low complexity transmission schemes applicable
to massive MIMO systems in upcoming 5G wireless networks is provided in the
first time. Moreover, adaptive transmission designs which switch among these
criteria based on the channel conditions to formulate the best transmission
strategy are discussed. Then, we provide a survey of the transmission designs
with discrete input signals for multiuser MIMO scenarios, including MIMO uplink
transmission, MIMO downlink transmission, MIMO interference channel, and MIMO
wiretap channel. Additionally, we discuss the transmission designs with
discrete input signals for other systems using MIMO technology. Finally,
technical challenges which remain unresolved at the time of writing are
summarized and the future trends of transmission designs with discrete input
signals are addressed.Comment: 110 pages, 512 references, submit to Proceedings of the IEE
A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels
In this paper, we establish a general framework on the reduced dimensional
channel state information (CSI) estimation and pre-beamformer design for
frequency-selective massive multiple-input multiple-output MIMO systems
employing single-carrier (SC) modulation in time division duplex (TDD) mode by
exploiting the joint angle-delay domain channel sparsity in millimeter (mm)
wave frequencies. First, based on a generic subspace projection taking the
joint angle-delay power profile and user-grouping into account, the reduced
rank minimum mean square error (RR-MMSE) instantaneous CSI estimator is derived
for spatially correlated wideband MIMO channels. Second, the statistical
pre-beamformer design is considered for frequency-selective SC massive MIMO
channels. We examine the dimension reduction problem and subspace (beamspace)
construction on which the RR-MMSE estimation can be realized as accurately as
possible. Finally, a spatio-temporal domain correlator type reduced rank
channel estimator, as an approximation of the RR-MMSE estimate, is obtained by
carrying out least square (LS) estimation in a proper reduced dimensional
beamspace. It is observed that the proposed techniques show remarkable
robustness to the pilot interference (or contamination) with a significant
reduction in pilot overhead
Area Rate Evaluation based on Spatial Clustering of massive MIMO Channel Measurements
Channel models for massive MIMO are typically based on matrices with complex
Gaussian entries, extended by the Kronecker and Weichselberger model. One
reason for observing a gap between modeled and actual channel behavior is the
absence of spatial consistency in many such models, that is, spatial
correlations over an area in the x, y-dimensions are not accounted for, making
it difficult to study, e.g., area-throughput measures. In this paper, we
propose an algorithm that can distinguish between regions of non-line-of-sight
(NLoS) and line-of-sight (LoS) via a rank-metric criterion combined with a
spiral search. With a k-means clustering algorithm a throughput per region
(i.e., cluster) can be calculated, leading to what we refer to as
"area-throughput". For evaluating the proposed orthogonality clustering scheme
we use a simple filtered MIMO channel model which is spatially consistent, with
known degrees of freedom. Moreover, we employ actual (spatially consistent)
area channel measurements based on spatial sampling using a spider antenna and
show that the proposed algorithm can be used to estimate the degrees of
freedom, and, subsequently, the number of users that maximizes the throughput
per square meter.Comment: Submitted to WSA201
Tucker Decomposition For Rotated Codebook in 3D MIMO System Under Spatially Correlated Channel
This correspondence proposes a new rotated codebook for three-dimensional
(3D) multi-input-multi-output (MIMO) system under spatially correlated channel.
To avoid the problem of high dimensionality led by large antenna array, the
rotation matrix in the rotated codebook is proposed to be decomposed by Tucker
decomposition into three lowdimensional units, i.e., statistical channel
direction information in horizontal and vertical directions respectively, and
statistical channel power in the joint horizontal and vertical direction. A
closed-form suboptimal solution is provided to reduce the computational
complexity in Tucker decomposition. The proposed codebook has a significant
dimension reduction from conventional rotated codebooks, and is applicable for
3D MIMO system with arbitrary form of antenna array. Simulation results
demonstrate that the proposed codebook works very well for various 3D MIMO
systems.Comment: accepted by IEEE Transactions on Vehicular Technolog
Principal Component Analysis (PCA)-based Massive-MIMO Channel Feedback
Channel-state-information (CSI) feedback methods are considered, especially
for massive or very large-scale multiple-input multiple-output (MIMO) systems.
To extract essential information from the CSI without redundancy that arises
from the highly correlated antennas, a receiver transforms (sparsifies) a
correlated CSI vector to an uncorrelated sparse CSI vector by using a
Karhunen-Loeve transform (KLT) matrix that consists of the eigen vectors of
covariance matrix of CSI vector and feeds back the essential components of the
sparse CSI, i.e., a principal component analysis method. A transmitter then
recovers the original CSI through the inverse transformation of the feedback
vector. Herein, to obtain the covariance matrix at transceiver, we derive
analytically the covariance matrix of spatially correlated Rayleigh fading
channels based on its statistics including transmit antennas' and receive
antennas' correlation matrices, channel variance, and channel delay profile.
With the knowledge of the channel statistics, the transceiver can readily
obtain the covariance matrix and KLT matrix. Compression feedback error and
bit-error-rate performance of the proposed method are analyzed. Numerical
results verify that the proposed method is promising, which reduces
significantly the feedback overhead of the massive-MIMO systems with marginal
performance degradation from full-CSI feedback (e.g., feedback amount reduction
by 80%, i.e., 1/5 of original CSI, with spectral efficiency reduction by only
2%). Furthermore, we show numerically that, for a given limited feedback
amount, we can find the optimal number of transmit antennas to achieve the
largest spectral efficiency, which is a new design framework.Comment: 10 pages, 5 figure
A Generalized Spatial Correlation Model for 3D MIMO Channels based on the Fourier Coefficients of Power Spectrums
Previous studies have confirmed the adverse impact of fading correlation on
the mutual information (MI) of two-dimensional (2D) multiple-input
multiple-output (MIMO) systems. More recently, the trend is to enhance the
system performance by exploiting the channel's degrees of freedom in the
elevation, which necessitates the derivation and characterization of
three-dimensional (3D) channels in the presence of spatial correlation. In this
paper, an exact closed-form expression for the Spatial Correlation Function
(SCF) is derived for 3D MIMO channels. This novel SCF is developed for a
uniform linear array of antennas with nonisotropic antenna patterns. The
proposed method resorts to the spherical harmonic expansion (SHE) of plane
waves and the trigonometric expansion of Legendre and associated Legendre
polynomials. The resulting expression depends on the underlying arbitrary
angular distributions and antenna patterns through the Fourier Series (FS)
coefficients of power azimuth and elevation spectrums. The novelty of the
proposed method lies in the SCF being valid for any 3D propagation environment.
The developed SCF determines the covariance matrices at the transmitter and the
receiver that form the Kronecker channel model. In order to quantify the
effects of correlation on the system performance, the information-theoretic
deterministic equivalents of the MI for the Kronecker model are utilized in
both mono-user and multi-user cases. Numerical results validate the proposed
analytical expressions and elucidate the dependence of the system performance
on azimuth and elevation angular spreads and antenna patterns. Some useful
insights into the behaviour of MI as a function of downtilt angles are
provided. The derived model will help evaluate the performance of correlated 3D
MIMO channels in the future.Comment: Accepted in IEEE Transactions on signal processin
Precoder Design for Multi-antenna Partial Decode-and-Forward (PDF) Cooperative Systems with Statistical CSIT and MMSE-SIC Receivers
Cooperative communication is an important technology in next generation
wireless networks. Aside from conventional amplify-and-forward (AF) and
decode-and-forward (DF) protocols, the partial decode-and-forward (PDF)
protocol is an alternative relaying scheme that is especially promising for
scenarios in which the relay node cannot reliably decode the complete source
message. However, there are several important issues to be addressed regarding
the application of PDF protocols. In this paper, we propose a PDF protocol and
MIMO precoder designs at the source and relay nodes. The precoder designs are
adapted based on statistical channel state information for correlated MIMO
channels, and matched to practical minimum mean-square-error successive
interference cancelation (MMSE-SIC) receivers at the relay and destination
nodes. We show that under similar system settings, the proposed MIMO precoder
design with PDF protocol and MMSE-SIC receivers achieves substantial
performance enhancement compared with conventional baselines
Linear Precoding for the MIMO Multiple Access Channel with Finite Alphabet Inputs and Statistical CSI
In this paper, we investigate the design of linear precoders for the
multiple-input multiple-output (MIMO) multiple access channel (MAC). We assume
that statistical channel state information (CSI) is available at the
transmitters and consider the problem under the practical finite alphabet input
assumption. First, we derive an asymptotic (in the large system limit)
expression for the weighted sum rate (WSR) of the MIMO MAC with finite alphabet
inputs and Weichselberger's MIMO channel model. Subsequently, we obtain the
optimal structures of the linear precoders of the users maximizing the
asymptotic WSR and an iterative algorithm for determining the precoders. We
show that the complexity of the proposed precoder design is significantly lower
than that of MIMO MAC precoders designed for finite alphabet inputs and
instantaneous CSI. Simulation results for finite alphabet signalling indicate
that the proposed precoder achieves significant performance gains over existing
precoder designs.Comment: Accepted by IEEE Transactions on Wireless Communications. arXiv admin
note: substantial text overlap with arXiv:1401.540
Optimization of Massive Full-Dimensional MIMO for Positioning and Communication
Massive Full-Dimensional multiple-input multiple-output (FD-MIMO) base
stations (BSs) have the potential to bring multiplexing and coverage gains by
means of three-dimensional (3D) beamforming. Key technical challenges for their
deployment include the presence of limited-resolution front ends and the
acquisition of channel state information (CSI) at the BSs. This paper
investigates the use of FD-MIMO BSs to provide simultaneously high-rate data
communication and mobile 3D positioning in the downlink. The analysis
concentrates on the problem of beamforming design by accounting for imperfect
CSI acquisition via Time Division Duplex (TDD)-based training and for the
finite resolution of analog-to-digital converter (ADC) and digital-to-analog
converter (DAC) at the BSs. Both \textit{unstructured beamforming} and a
low-complexity \textit{Kronecker beamforming} solution are considered, where
for the latter the beamforming vectors are decomposed into separate azimuth and
elevation components. The proposed algorithmic solutions are based on Bussgang
theorem, rank-relaxation and successive convex approximation (SCA) methods.
Comprehensive numerical results demonstrate that the proposed schemes can
effectively cater to both data communication and positioning services,
providing only minor performance degradations as compared to the more
conventional cases in which either function is implemented. Moreover, the
proposed low-complexity Kronecker beamforming solutions are seen to guarantee a
limited performance loss in the presence of a large number of BS antennas.Comment: 30 pages, 6 figure
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