430 research outputs found
Learning and Designing Stochastic Processes from Logical Constraints
Stochastic processes offer a flexible mathematical formalism to model and
reason about systems. Most analysis tools, however, start from the premises
that models are fully specified, so that any parameters controlling the
system's dynamics must be known exactly. As this is seldom the case, many
methods have been devised over the last decade to infer (learn) such parameters
from observations of the state of the system. In this paper, we depart from
this approach by assuming that our observations are {\it qualitative}
properties encoded as satisfaction of linear temporal logic formulae, as
opposed to quantitative observations of the state of the system. An important
feature of this approach is that it unifies naturally the system identification
and the system design problems, where the properties, instead of observations,
represent requirements to be satisfied. We develop a principled statistical
estimation procedure based on maximising the likelihood of the system's
parameters, using recent ideas from statistical machine learning. We
demonstrate the efficacy and broad applicability of our method on a range of
simple but non-trivial examples, including rumour spreading in social networks
and hybrid models of gene regulation
Power Allocation in Two-Hop Amplify-and-Forward MIMO Relay Systems with QoS requirements
The problem of minimizing the total power consumption while satisfying
different quality-of-service (QoS) requirements in a two-hop multiple-input
multiple-output network with a single non-regenerative relay is considered. As
shown by Y. Rong in [1], the optimal processing matrices for both linear and
non-linear transceiver architectures lead to the diagonalization of the
source-relay-destination channel so that the power minimization problem reduces
to properly allocating the available power over the established links.
Unfortunately, finding the solution of this problem is numerically difficult as
it is not in a convex form. To overcome this difficulty, existing solutions
rely on the computation of upper- and lower-bounds that are hard to obtain or
require the relaxation of the QoS constraints. In this work, a novel approach
is devised for both linear and non-linear transceiver architectures, which
allows to closely approximate the solutions of the non-convex power allocation
problems with those of convex ones easy to compute in closed-form by means of
multi-step procedures of reduced complexity. Computer simulations are used to
assess the performance of the proposed approach and to make comparisons with
alternatives
Interference Management in 5G Reverse TDD HetNets with Wireless Backhaul: A Large System Analysis
This work analyzes a heterogeneous network (HetNet), which comprises a macro
base station (BS) equipped with a large number of antennas and an overlaid
dense tier of small cell access points (SCAs) using a wireless backhaul for
data traffic. The static and low mobility user equipment terminals (UEs) are
associated with the SCAs while those with medium-to-high mobility are served by
the macro BS. A reverse time division duplexing (TDD) protocol is used by the
two tiers, which allows the BS to locally estimate both the intra-tier and
inter-tier channels. This knowledge is then used at the BS either in the uplink
(UL) or in the downlink (DL) to simultaneously serve the macro UEs (MUEs) and
to provide the wireless backhaul to SCAs. A geographical separation of
co-channel SCAs is proposed to limit the interference coming from the UL
signals of MUEs. A concatenated linear precoding technique employing either
zero-forcing (ZF) or regularized ZF is used at the BS to simultaneously serve
MUEs and SCAs in DL while nulling interference toward those SCAs in UL. We
evaluate and characterize the performance of the system through the power
consumption of UL and DL transmissions under the assumption that target rates
must be satisfied and imperfect channel state information is available for
MUEs. The analysis is conducted in the asymptotic regime where the number of BS
antennas and the network size (MUEs and SCAs) grow large with fixed ratios.
Results from large system analysis are used to provide concise formulae for the
asymptotic UL and DL transmit powers and precoding vectors under the above
assumptions. Numerical results are used to validate the analysis in different
settings and to make comparisons with alternative network architectures.Comment: 14 pages, 12 figures. To appear IEEE J. Select. Areas Commun. --
Special Issue on HetNet
Can Hardware Distortion Correlation be Neglected When Analyzing Uplink SE in Massive MIMO?
This paper analyzes how the distortion created by hardware impairments in a
multiple-antenna base station affects the uplink spectral efficiency (SE), with
focus on Massive MIMO. The distortion is correlated across the antennas, but
has been often approximated as uncorrelated to facilitate (tractable) SE
analysis. To determine when this approximation is accurate, basic properties of
the distortion correlation are first uncovered. Then, we focus on third-order
non-linearities and prove analytically and numerically that the correlation can
be neglected in the SE analysis when there are many users. In i.i.d. Rayleigh
fading with equal signal-to-noise ratios, this occurs when having five users.Comment: 5 pages, 3 figures, IEEE International Workshop on Signal Processing
Advances in Wireless Communications (SPAWC), 201
Massive MIMO has Unlimited Capacity
The capacity of cellular networks can be improved by the unprecedented array
gain and spatial multiplexing offered by Massive MIMO. Since its inception, the
coherent interference caused by pilot contamination has been believed to create
a finite capacity limit, as the number of antennas goes to infinity. In this
paper, we prove that this is incorrect and an artifact from using simplistic
channel models and suboptimal precoding/combining schemes. We show that with
multicell MMSE precoding/combining and a tiny amount of spatial channel
correlation or large-scale fading variations over the array, the capacity
increases without bound as the number of antennas increases, even under pilot
contamination. More precisely, the result holds when the channel covariance
matrices of the contaminating users are asymptotically linearly independent,
which is generally the case. If also the diagonals of the covariance matrices
are linearly independent, it is sufficient to know these diagonals (and not the
full covariance matrices) to achieve an unlimited asymptotic capacity.Comment: To appear in IEEE Transactions on Wireless Communications, 17 pages,
7 figure
Asymptotic Analysis of Multicell Massive MIMO over Rician Fading Channels
This work considers the downlink of a multicell massive MIMO system in which
base stations (BSs) of antennas each communicate with
single-antenna user equipments randomly positioned in the coverage area. Within
this setting, we are interested in evaluating the sum rate of the system when
MRT and RZF are employed under the assumption that each intracell link forms a
MIMO Rician fading channel. The analysis is conducted assuming that and
grow large with a non-trivial ratio under the assumption that the data
transmission in each cell is affected by channel estimation errors, pilot
contamination, and an arbitrary large scale attenuation. Numerical results are
used to validate the asymptotic analysis in the finite system regime and to
evaluate the network performance under different settings. The asymptotic
results are also instrumental to get insights into the interplay among system
parameters.Comment: 7 pages, 2 figures, submitted to GLOBECOM16, Washington, DC USA.
arXiv admin note: text overlap with arXiv:1601.0702
Energy-Efficient Future Wireless Networks: A Marriage between Massive MIMO and Small Cells
How would a cellular network designed for high energy efficiency look like?
To answer this fundamental question, we model cellular networks using
stochastic geometry and optimize the energy efficiency with respect to the
density of base stations, the number of antennas and users per cell, the
transmit power levels, and the pilot reuse. The highest efficiency is neither
achieved by a pure small-cell approach, nor by a pure massive MIMO solution.
Interestingly, it is the combination of these approaches that provides the
highest energy efficiency; small cells contributes by reducing the propagation
losses while massive MIMO enables multiplexing of users with controlled
interference.Comment: Published at IEEE Workshop on Signal Processing Advances in Wireless
Communications (SPAWC 2015), 5 pages, 5 figure
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