28,662 research outputs found
Pilot Decontamination Through Pilot Sequence Hopping in Massive MIMO Systems
This work concerns wireless cellular networks applying massive multiple-input
multiple-output (MIMO) technology. In such a system, the base station in a
given cell is equipped with a very large number (hundreds or even thousands) of
antennas and serves multiple users. Estimation of the channel from the base
station to each user is performed at the base station using an uplink pilot
sequence. Such a channel estimation procedure suffers from pilot contamination.
Orthogonal pilot sequences are used in a given cell but, due to the shortage of
orthogonal sequences, the same pilot sequences must be reused in neighboring
cells, causing pilot contamination. The solution presented in this paper
suppresses pilot contamination, without the need for coordination among cells.
Pilot sequence hopping is performed at each transmission slot, which provides a
randomization of the pilot contamination. Using a modified Kalman filter, it is
shown that such randomized contamination can be significantly suppressed.
Comparisons with conventional estimation methods show that the mean squared
error can be lowered as much as an order of magnitude at low mobility
Log Skeletons: A Classification Approach to Process Discovery
To test the effectiveness of process discovery algorithms, a Process
Discovery Contest (PDC) has been set up. This PDC uses a classification
approach to measure this effectiveness: The better the discovered model can
classify whether or not a new trace conforms to the event log, the better the
discovery algorithm is supposed to be. Unfortunately, even the state-of-the-art
fully-automated discovery algorithms score poorly on this classification. Even
the best of these algorithms, the Inductive Miner, scored only 147 correct
classified traces out of 200 traces on the PDC of 2017. This paper introduces
the rule-based log skeleton model, which is closely related to the Declare
constraint model, together with a way to classify traces using this model. This
classification using log skeletons is shown to score better on the PDC of 2017
than state-of-the-art discovery algorithms: 194 out of 200. As a result, one
can argue that the fully-automated algorithm to construct (or: discover) a log
skeleton from an event log outperforms existing state-of-the-art
fully-automated discovery algorithms.Comment: 16 pages with 9 figures, followed by an appendix of 14 pages with 17
figure
Massive MIMO for Crowd Scenarios: A Solution Based on Random Access
This paper presents a new approach to intra-cell pilot contamination in
crowded massive MIMO scenarios. The approach relies on two essential properties
of a massive MIMO system, namely near-orthogonality between user channels and
near-stability of channel powers. Signal processing techniques that take
advantage of these properties allow us to view a set of contaminated pilot
signals as a graph code on which iterative belief propagation can be performed.
This makes it possible to decontaminate pilot signals and increase the
throughput of the system. The proposed solution exhibits high performance with
large improvements over the conventional method. The improvements come at the
price of an increased error rate, although this effect is shown to decrease
significantly for increasing number of antennas at the base station
Charge orders, magnetism and pairings in the cuprate superconductors
We review the recent developments in the field of cuprate superconductors
with the special focus on the recently observed charge order in the underdoped
compounds. We introduce new theoretical developments following the study of the
antiferromagnetic (AF) quantum critical point (QCP) in two dimensions, in which
preemptive orders in the charge and superconducting (SC) sectors emerged, that
are in turn related by an SU(2) symmetry. We consider the implications of this
proliferation of orders in the underdoped region, and provide a study of the
type of fluctuations which characterize the SU(2) symmetry. We identify an
intermediate energy scale where the SU(2) pairing fluctuations are dominant and
argue that they are unstable towards the formation of a Resonant Peierls
Excitonic (RPE) state at the pseudogap (PG) temperature . We discuss the
implications of this scenario for a few key experiments.Comment: 16 pages, 17 figure
A Random Access Protocol for Pilot Allocation in Crowded Massive MIMO Systems
The Massive MIMO (multiple-input multiple-output) technology has great
potential to manage the rapid growth of wireless data traffic. Massive MIMO
achieves tremendous spectral efficiency by spatial multiplexing of many tens of
user equipments (UEs). These gains are only achieved in practice if many more
UEs can connect efficiently to the network than today. As the number of UEs
increases, while each UE intermittently accesses the network, the random access
functionality becomes essential to share the limited number of pilots among the
UEs. In this paper, we revisit the random access problem in the Massive MIMO
context and develop a reengineered protocol, termed strongest-user collision
resolution (SUCRe). An accessing UE asks for a dedicated pilot by sending an
uncoordinated random access pilot, with a risk that other UEs send the same
pilot. The favorable propagation of Massive MIMO channels is utilized to enable
distributed collision detection at each UE, thereby determining the strength of
the contenders' signals and deciding to repeat the pilot if the UE judges that
its signal at the receiver is the strongest. The SUCRe protocol resolves the
vast majority of all pilot collisions in crowded urban scenarios and continues
to admit UEs efficiently in overloaded networks.Comment: To appear in IEEE Transactions on Wireless Communications, 16 pages,
10 figures. This is reproducible research with simulation code available at
https://github.com/emilbjornson/sucre-protoco
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