387 research outputs found
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
Bit-Interleaved Coded Modulation Revisited: A Mismatched Decoding Perspective
We revisit the information-theoretic analysis of bit-interleaved coded
modulation (BICM) by modeling the BICM decoder as a mismatched decoder. The
mismatched decoding model is well-defined for finite, yet arbitrary, block
lengths, and naturally captures the channel memory among the bits belonging to
the same symbol. We give two independent proofs of the achievability of the
BICM capacity calculated by Caire et al. where BICM was modeled as a set of
independent parallel binary-input channels whose output is the bitwise
log-likelihood ratio. Our first achievability proof uses typical sequences, and
shows that due to the random coding construction, the interleaver is not
required. The second proof is based on the random coding error exponents with
mismatched decoding, where the largest achievable rate is the generalized
mutual information. We show that the generalized mutual information of the
mismatched decoder coincides with the infinite-interleaver BICM capacity. We
also show that the error exponent -and hence the cutoff rate- of the BICM
mismatched decoder is upper bounded by that of coded modulation and may thus be
lower than in the infinite-interleaved model. We also consider the mutual
information appearing in the analysis of iterative decoding of BICM with EXIT
charts. We show that the corresponding symbol metric has knowledge of the
transmitted symbol and the EXIT mutual information admits a representation as a
pseudo-generalized mutual information, which is in general not achievable. A
different symbol decoding metric, for which the extrinsic side information
refers to the hypothesized symbol, induces a generalized mutual information
lower than the coded modulation capacity.Comment: submitted to the IEEE Transactions on Information Theory. Conference
version in 2008 IEEE International Symposium on Information Theory, Toronto,
Canada, July 200
Bit-interleaved coded modulation in the wideband regime
The wideband regime of bit-interleaved coded modulation (BICM) in Gaussian
channels is studied. The Taylor expansion of the coded modulation capacity for
generic signal constellations at low signal-to-noise ratio (SNR) is derived and
used to determine the corresponding expansion for the BICM capacity. Simple
formulas for the minimum energy per bit and the wideband slope are given. BICM
is found to be suboptimal in the sense that its minimum energy per bit can be
larger than the corresponding value for coded modulation schemes. The minimum
energy per bit using standard Gray mapping on M-PAM or M^2-QAM is given by a
simple formula and shown to approach -0.34 dB as M increases. Using the low SNR
expansion, a general trade-off between power and bandwidth in the wideband
regime is used to show how a power loss can be traded off against a bandwidth
gain.Comment: Submitted to IEEE Transactions on Information Theor
Living at the Edge: A Large Deviations Approach to the Outage MIMO Capacity
Using a large deviations approach we calculate the probability distribution
of the mutual information of MIMO channels in the limit of large antenna
numbers. In contrast to previous methods that only focused at the distribution
close to its mean (thus obtaining an asymptotically Gaussian distribution), we
calculate the full distribution, including its tails which strongly deviate
from the Gaussian behavior near the mean. The resulting distribution
interpolates seamlessly between the Gaussian approximation for rates close
to the ergodic value of the mutual information and the approach of Zheng and
Tse for large signal to noise ratios . This calculation provides us with
a tool to obtain outage probabilities analytically at any point in the parameter space, as long as the number of antennas is not too
small. In addition, this method also yields the probability distribution of
eigenvalues constrained in the subspace where the mutual information per
antenna is fixed to for a given . Quite remarkably, this eigenvalue
density is of the form of the Marcenko-Pastur distribution with square-root
singularities, and it depends on the values of and .Comment: Accepted for publication, IEEE Transactions on Information Theory
(2010). Part of this work appears in the Proc. IEEE Information Theory
Workshop, June 2009, Volos, Greec
Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas
The main focus and contribution of this paper is a novel network-MIMO TDD
architecture that achieves spectral efficiencies comparable with "Massive
MIMO", with one order of magnitude fewer antennas per active user per cell. The
proposed architecture is based on a family of network-MIMO schemes defined by
small clusters of cooperating base stations, zero-forcing multiuser MIMO
precoding with suitable inter-cluster interference constraints, uplink pilot
signals reuse across cells, and frequency reuse. The key idea consists of
partitioning the users population into geographically determined "bins", such
that all users in the same bin are statistically equivalent, and use the
optimal network-MIMO architecture in the family for each bin. A scheduler takes
care of serving the different bins on the time-frequency slots, in order to
maximize a desired network utility function that captures some desired notion
of fairness. This results in a mixed-mode network-MIMO architecture, where
different schemes, each of which is optimized for the served user bin, are
multiplexed in time-frequency. In order to carry out the performance analysis
and the optimization of the proposed architecture in a clean and
computationally efficient way, we consider the large-system regime where the
number of users, the number of antennas, and the channel coherence block length
go to infinity with fixed ratios. The performance predicted by the large-system
asymptotic analysis matches very well the finite-dimensional simulations.
Overall, the system spectral efficiency obtained by the proposed architecture
is similar to that achieved by "Massive MIMO", with a 10-fold reduction in the
number of antennas at the base stations (roughly, from 500 to 50 antennas).Comment: Full version with appendice (proofs of theorems). A shortened version
without appendice was submitted to IEEE Trans. on Wireless Commun. Appendix B
was revised after submissio
Joint Scheduling and ARQ for MU-MIMO Downlink in the Presence of Inter-Cell Interference
User scheduling and multiuser multi-antenna (MU-MIMO) transmission are at the
core of high rate data-oriented downlink schemes of the next-generation of
cellular systems (e.g., LTE-Advanced). Scheduling selects groups of users
according to their channels vector directions and SINR levels. However, when
scheduling is applied independently in each cell, the inter-cell interference
(ICI) power at each user receiver is not known in advance since it changes at
each new scheduling slot depending on the scheduling decisions of all
interfering base stations. In order to cope with this uncertainty, we consider
the joint operation of scheduling, MU-MIMO beamforming and Automatic Repeat
reQuest (ARQ). We develop a game-theoretic framework for this problem and build
on stochastic optimization techniques in order to find optimal scheduling and
ARQ schemes. Particularizing our framework to the case of "outage service
rates", we obtain a scheme based on adaptive variable-rate coding at the
physical layer, combined with ARQ at the Logical Link Control (ARQ-LLC). Then,
we present a novel scheme based on incremental redundancy Hybrid ARQ (HARQ)
that is able to achieve a throughput performance arbitrarily close to the
"genie-aided service rates", with no need for a genie that provides
non-causally the ICI power levels. The novel HARQ scheme is both easier to
implement and superior in performance with respect to the conventional
combination of adaptive variable-rate coding and ARQ-LLC.Comment: Submitted to IEEE Transactions on Communications, v2: small
correction
- âŠ