4,196 research outputs found
Impact of Spatial Correlation on the Finite-SNR Diversity-Multiplexing Tradeoff
The impact of spatial correlation on the performance limits of multielement
antenna (MEA) channels is analyzed in terms of the diversity-multiplexing
tradeoff (DMT) at finite signal-to-noise ratio (SNR) values. A lower bound on
the outage probability is first derived. Using this bound accurate finite-SNR
estimate of the DMT is then derived. This estimate allows to gain insight on
the impact of spatial correlation on the DMT at finite SNR. As expected, the
DMT is severely degraded as the spatial correlation increases. Moreover, using
asymptotic analysis, we show that our framework encompasses well-known results
concerning the asymptotic behavior of the DMT.Comment: Accepted for publication to IEEE Transaction on Wireless
Communication on June 4th 200
Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities
Recently there has been a flurry of research on the use of reconfigurable
intelligent surfaces (RIS) in wireless networks to create smart radio
environments. In a smart radio environment, surfaces are capable of
manipulating the propagation of incident electromagnetic waves in a
programmable manner to actively alter the channel realization, which turns the
wireless channel into a controllable system block that can be optimized to
improve overall system performance. In this article, we provide a tutorial
overview of reconfigurable intelligent surfaces (RIS) for wireless
communications. We describe the working principles of reconfigurable
intelligent surfaces (RIS) and elaborate on different candidate implementations
using metasurfaces and reflectarrays. We discuss the channel models suitable
for both implementations and examine the feasibility of obtaining accurate
channel estimates. Furthermore, we discuss the aspects that differentiate RIS
optimization from precoding for traditional MIMO arrays highlighting both the
arising challenges and the potential opportunities associated with this
emerging technology. Finally, we present numerical results to illustrate the
power of an RIS in shaping the key properties of a MIMO channel.Comment: to appear in the IEEE Transactions on Cognitive Communications and
Networking (TCCN
Modeling of wide-band MIMO radio channels based on NLoS indoor measurements
Link to published version (if available)
Asymptotic Performance of Linear Receivers in MIMO Fading Channels
Linear receivers are an attractive low-complexity alternative to optimal
processing for multi-antenna MIMO communications. In this paper we characterize
the information-theoretic performance of MIMO linear receivers in two different
asymptotic regimes. For fixed number of antennas, we investigate the limit of
error probability in the high-SNR regime in terms of the Diversity-Multiplexing
Tradeoff (DMT). Following this, we characterize the error probability for fixed
SNR in the regime of large (but finite) number of antennas.
As far as the DMT is concerned, we report a negative result: we show that
both linear Zero-Forcing (ZF) and linear Minimum Mean-Square Error (MMSE)
receivers achieve the same DMT, which is largely suboptimal even in the case
where outer coding and decoding is performed across the antennas. We also
provide an approximate quantitative analysis of the markedly different behavior
of the MMSE and ZF receivers at finite rate and non-asymptotic SNR, and show
that while the ZF receiver achieves poor diversity at any finite rate, the MMSE
receiver error curve slope flattens out progressively, as the coding rate
increases.
When SNR is fixed and the number of antennas becomes large, we show that the
mutual information at the output of a MMSE or ZF linear receiver has
fluctuations that converge in distribution to a Gaussian random variable, whose
mean and variance can be characterized in closed form. This analysis extends to
the linear receiver case a well-known result previously obtained for the
optimal receiver. Simulations reveal that the asymptotic analysis captures
accurately the outage behavior of systems even with a moderate number of
antennas.Comment: 48 pages, Submitted to IEEE Transactions on Information Theor
Fundamental Limits in Correlated Fading MIMO Broadcast Channels: Benefits of Transmit Correlation Diversity
We investigate asymptotic capacity limits of the Gaussian MIMO broadcast
channel (BC) with spatially correlated fading to understand when and how much
transmit correlation helps the capacity. By imposing a structure on channel
covariances (equivalently, transmit correlations at the transmitter side) of
users, also referred to as \emph{transmit correlation diversity}, the impact of
transmit correlation on the power gain of MIMO BCs is characterized in several
regimes of system parameters, with a particular interest in the large-scale
array (or massive MIMO) regime. Taking the cost for downlink training into
account, we provide asymptotic capacity bounds of multiuser MIMO downlink
systems to see how transmit correlation diversity affects the system
multiplexing gain. We make use of the notion of joint spatial division and
multiplexing (JSDM) to derive the capacity bounds. It is advocated in this
paper that transmit correlation diversity may be of use to significantly
increase multiplexing gain as well as power gain in multiuser MIMO systems. In
particular, the new type of diversity in wireless communications is shown to
improve the system multiplexing gain up to by a factor of the number of degrees
of such diversity. Finally, performance limits of conventional large-scale MIMO
systems not exploiting transmit correlation are also characterized.Comment: 29 pages, 8 figure
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