pwc-archive/papers-with-abstracts huggingface dataset:
Technical Report on Efficient Integration of Dynamic TDD with Massive MIMO
Date: 2018-04-17 00:00:00

Recent advances in massive multiple-input multiple-output (MIMO)
communication show that equipping base stations (BSs) with large arrays of
antenna can significantly improve the performance of cellular networks. Massive
MIMO has the potential to mitigate the interference in the network and enhance
the average throughput per user. On the other hand, dynamic time division
duplexing (TDD), which allows neighboring cells to operate with different
uplink (UL) and downlink (DL) sub-frame configurations, is a promising
enhancement for the conventional static TDD. Compared with static TDD, dynamic
TDD can offer more flexibility to accommodate various UL and DL traffic
patterns across different cells, but may result in additional interference
among cells transmitting in different directions. Based on the unique
characteristics and properties of massive MIMO and dynamic TDD, we propose a
marriage of these two techniques, i.e., to have massive MIMO address the
limitation of dynamic TDD in macro cell (MC) networks. Specifically, we
advocate that the benefits of dynamic TDD can be fully extracted in MC networks
equipped with massive MIMO, i.e., the BS-to-BS interference can be effectively
removed by increasing the number of BS antennas. We provide detailed analysis
using random matrix theory to show that the effect of the BS-to-BS interference
on uplink transmissions vanishes as the number of BS antennas per-user grows
infinitely large. Last but not least, we validate our analysis by numerical
simulations.
Precise Detection of Speech Endpoints Dynamically: A Wavelet Convolution based approach
Date: 2018-04-17 00:00:00
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), speech-recognition, Speech Recognition

Precise detection of speech endpoints is an important factor which affects
the performance of the systems where speech utterances need to be extracted
from the speech signal such as Automatic Speech Recognition (ASR) system.
Existing endpoint detection (EPD) methods mostly uses Short-Term Energy (STE),
Zero-Crossing Rate (ZCR) based approaches and their variants. But STE and ZCR
based EPD algorithms often fail in the presence of Non-speech Sound Artifacts
(NSAs) produced by the speakers. Algorithms based on pattern recognition and
classification techniques are also proposed but require labeled data for
training. A new algorithm termed as Wavelet Convolution based Speech Endpoint
Detection (WCSEPD) is proposed in this article to extract speech endpoints.
WCSEPD decomposes the speech signal into high-frequency and low-frequency
components using wavelet convolution and computes entropy based thresholds for
the two frequency components. The low-frequency thresholds are used to extract
voiced speech segments, whereas the high-frequency thresholds are used to
extract the unvoiced speech segments by filtering out the NSAs. WCSEPD does not
require any labeled data for training and can automatically extract speech
segments. Experiment results show that the proposed algorithm precisely
extracts speech endpoints in the presence of NSAs.
Sensitivity to initial conditions in an extended activator-inhibitor model for the formation of patterns
Date: 2018-07-10 00:00:00
Tasks: Math, Sensitivity

Despite simplicity, the synchronous cellular automaton [D.A. Young, Math.
Biosci. 72, 51 (1984)] enables reconstructing basic features of patterns of
skin. Our extended model allows studying the formatting of patterns and their
temporal evolution also on the favourable and hostile environments. As a
result, the impact of different types of an environment is accounted for the
dynamics of patterns formation. The process is based on two diffusible
morphogens, the short-range activator and the long-range inhibitor, produced by
differentiated cells (DCs) represented as black pixels. For a neutral
environment, the extended model reduces to the original one. However, even the
reduced model is statistically sensitive to a type of the initial distribution
of DCs. To compare the impact of the uniform random distribution of DCs
(R-system) and the non-uniform distribution in the form of random
Gaussian-clusters (G-system), we chose inhibitor as the control parameter. To
our surprise, in the neutral environment, for the chosen inhibitor-value that
ensures stable final patterns, the average size of final G-populations is lower
than in the R-case. In turn, when we consider the favourable environment, the
relatively bigger shift toward higher final concentrations of DCs appears in
the G. Thus, in the suitably favourable environment, this order can be
reversed. Furthermore, the different critical values of the control parameter
for the R and the G suggest some dissimilarities in temporal evolution of both
systems. In particular, within the proper ranges of the critical values, their
oscillatory behaviours are different. The respective temporal evolutions are
illustrated by a few examples.
Joint Beam and Channel Tracking for Two-Dimensional Phased Antenna Arrays
Date: 2018-12-27 00:00:00
Tasks: Vocal Bursts Valence Prediction

Analog beamforming is a low-cost architecture for millimeter-wave (mmWave)
mobile communications. However, it has two disadvantages for serving fast
mobility users: (i) the mmWave beam in the wireless channel and the beam
steered by analog beamforming have small angular spreads which are difficult to
align with each other and (ii) the receiver can only observe the mmWave channel
in one beam direction and rely on beam-probing algorithms to check other
directions. In this paper, we develop a beam probing and tracking algorithm
that can efficiently track fast-moving mmWave beams in three-dimensional (3D)
space. This algorithm has several salient features: (1) fading channel
supportive: it can simultaneously track the channel coefficient and
two-dimensional (2D) beam direction in fading channel environments; (2) low
probing overhead: it achieves the minimum probing requirement for joint beam
and channel tracking; (3) fast tracking speed and high tracking accuracy: its
tracking error converges to the minimum Cramer-Rao lower bound (CRLB) in static
scenarios in theory and it outperforms several existing tracking algorithms
with lower tracking error and faster tracking speed in simulations.
Dissection of Bitcoin's Multiscale Bubble History from January 2012 to February 2018
Date: 2019-05-30 00:00:00
Tasks: Time Series Analysis

We present a detailed bubble analysis of the Bitcoin to US Dollar price
dynamics from January 2012 to February 2018. We introduce a robust automatic
peak detection method that classifies price time series into periods of
uninterrupted market growth (drawups) and regimes of uninterrupted market
decrease (drawdowns). In combination with the Lagrange Regularisation Method
for detecting the beginning of a new market regime, we identify 3 major peaks
and 10 additional smaller peaks, that have punctuated the dynamics of Bitcoin
price during the analyzed time period. We explain this classification of long
and short bubbles by a number of quantitative metrics and graphs to understand
the main socio-economic drivers behind the ascent of Bitcoin over this period.
Then, a detailed analysis of the growing risks associated with the three long
bubbles using the Log-Periodic Power Law Singularity (LPPLS) model is based on
the LPPLS Confidence Indicators, defined as the fraction of qualified fits of
the LPPLS model over multiple time windows. Furthermore, for various fictitious
'present' times $t_2$ before the crashes, we employ a clustering method to
group the predicted critical times $t_c$ of the LPPLS fits over different time
scales, where $t_c$ is the most probable time for the ending of the bubble.
Each cluster is proposed as a plausible scenario for the subsequent Bitcoin
price evolution. We present these predictions for the three long bubbles and
the four short bubbles that our time scale of analysis was able to resolve.
Overall, our predictive scheme provides useful information to warn of an
imminent crash risk.
Revisiting the thermal and superthermal two-class distribution of incomes: A critical perspective
Date: 2018-04-17 00:00:00

This paper offers a two-pronged critique of the empirical investigation of
the income distribution performed by physicists over the past decade. Their
finding rely on the graphical analysis of the observed distribution of
normalized incomes. Two central observations lead to the conclusion that the
majority of incomes are exponentially distributed, but neither each individual
piece of evidence nor their concurrent observation robustly proves that the
thermal and superthermal mixture fits the observed distribution of incomes
better than reasonable alternatives. A formal analysis using popular measures
of fit shows that while an exponential distribution with a power-law tail
provides a better fit of the IRS income data than the log-normal distribution
(often assumed by economists), the thermal and superthermal mixture's fit can
be improved upon further by adding a log-normal component. The economic
implications of the thermal and superthermal distribution of incomes, and the
expanded mixture are explored in the paper.
Contextualised Browsing in a Digital Library's Living Lab
Authors: Carevic Zeljko, Schüller Sascha, Mayr Philipp, Fuhr Norbert
Date: 2018-04-17 00:00:00
Tasks: Re-Ranking, Retrieval

Contextualisation has proven to be effective in tailoring \linebreak search
results towards the users' information need. While this is true for a basic
query search, the usage of contextual session information during exploratory
search especially on the level of browsing has so far been underexposed in
research. In this paper, we present two approaches that contextualise browsing
on the level of structured metadata in a Digital Library (DL), (1) one variant
bases on document similarity and (2) one variant utilises implicit session
information, such as queries and different document metadata encountered during
the session of a users. We evaluate our approaches in a living lab environment
using a DL in the social sciences and compare our contextualisation approaches
against a non-contextualised approach. For a period of more than three months
we analysed 47,444 unique retrieval sessions that contain search activities on
the level of browsing. Our results show that a contextualisation of browsing
significantly outperforms our baseline in terms of the position of the first
clicked item in the result set. The mean rank of the first clicked document
(measured as mean first relevant - MFR) was 4.52 using a non-contextualised
ranking compared to 3.04 when re-ranking the result lists based on similarity
to the previously viewed document. Furthermore, we observed that both
contextual approaches show a noticeably higher click-through rate. A
contextualisation based on document similarity leads to almost twice as many
document views compared to the non-contextualised ranking.
Elongation and shape changes in organisms with cell walls: a dialogue between experiments and models
Date: 2018-04-17 00:00:00

The generation of anisotropic shapes occurs during morphogenesis of almost
all organisms. With the recent renewal of the interest in mechanical aspects of
morphogenesis, it has become clear that mechanics contributes to anisotropic
forms in a subtle interaction with various molecular actors. Here, we consider
plants, fungi, oomycetes, and bacteria, and we review the mechanisms by which
elongated shapes are generated and maintained. We focus on theoretical models
of the interplay between growth and mechanics, in relation with experimental
data, and discuss how models may help us improve our understanding of the
underlying biological mechanisms.
How should fishing mortality be distributed under balanced harvesting?
Date: 2019-10-22 00:00:00

Zhou and Smith (2017) investigate different multi-species harvesting
scenarios using a simple Holling-Tanner model. Among these scenarios are two
methods for implementing balanced harvesting, where fishing is distributed
across trophic levels in accordance with their productivity. This note examines
the effects of a different quantitative implementation of balanced harvesting,
where the fishing mortality rate is proportional to the total production rate
of each trophic level. The results show that setting fishing mortality rate to
be proportional to total production rate, rather than to productivity per unit
biomass, better preserves trophic structure and provides a crucial safeguard
for rare and threatened ecological groups. This is a key ingredient of balanced
harvesting if it is to meet its objective of preserving biodiversity.
A Simple Channel Independent Beamforming Scheme with Circular Array
Date: 2018-04-18 00:00:00

In this letter, we consider a uniform circular array (UCA) based
line-of-sight (LOS) multiple-input-multiple-output (MIMO) system, where the
transmit and receive UCAs are aligned with each other. We propose a simple
channel independent beamforming scheme with fast symbol-wise maximum likelihood
(ML) detection.
Application of Vector Sensor for Underwater Acoustic Communications
Date: 2018-04-18 00:00:00
Tasks: Diversity

The use of vector sensors as receivers for Underwater Acoustic Communications
systems is gaining popularity. It has become important to obtain performance
measures for such communication systems to quantify their efficacy. The
fundamental advantage of using a vector sensor as a receiver is that a single
sensor is able to provide diversity gains offered by MIMO systems. In a recent
work novel framework for evaluating capacity of underwater channel was
proposed. The approach is based on modeling the channel as a set of paths along
which the signal arrives at the receiver with different Angles of Arrival. In
this work, we build on that framework to provide a bound on the achievable
capacity of such a system. The analytical bounds have been compared against
simulation results for a vector sensor based SIMO underwater communications
system. The channel parameters are modeled by analysing the statistics
generated with Bellhop simulation tool. This representation of the channel is
flexible and allows for characterizing channels at differenet geographical
locations and at different time instances. This characterization in terms of
channel parameters enables the computing of the performance measure (channel
capacity bound) for different geographical locations
Assessing the state of e-Readiness for Small and Medium Companies in Mexico: a Proposed Taxonomy and Adoption Model
Date: 2018-03-12 00:00:00
Tasks: Management

Emerging economies frequently show a large component of their Gross Domestic
Product to be dependant on the economic activity of small and medium
enterprises. Nevertheless, e-business solutions are more likely designed for
large companies. SMEs seem to follow a classical family-based management, used
to traditional activities, rather than seeking new ways of adding value to
their business strategy. Thus, a large portion of a nations economy may be at
disadvantage for competition. This paper aims at assessing the state of
e-business readiness of Mexican SMEs based on already published e-business
evolution models and by means of a survey research design. Data is being
collected in three cities with differing sizes and infrastructure conditions.
Statistical results are expected to be presented. A second part of this
research aims at applying classical adoption models to suggest potential causal
relationships, as well as more suitable recommendations for development.
An Attempt at Analyzing the Information Nature of Money
Date: 2018-03-26 00:00:00

Money was invented to address the difficulty in the double coincidence of
wants between the supply and demand when people exchanged their goods and
services. There are two information states in society: one is the initial state
that people have goods and services due to division of labor; the other is the
final state that people have different goods and services with the initial
state due to exchange of goods and services between them. The process is that
the initial state is changed to the final state with the help of money. Because
the direct exchanges of goods and services are difficult to achieve the double
coincidence of wants in time and space, it can be achieved with the help of
money which is as a medium and bridge. In this paper the changing process of
the state information is analyzed through the matrix representation of money,
and then the nature of money with a kind of information of reliable ledger is
more apparently shown. This paper also analyzes the common characteristics of
physical money, electronic money and digital currency, that is, reliable ledger
and explores the future trend of money development from the perspective of
history and security technology of money.
The CCI30 Index
Date: 2018-03-28 00:00:00

We describe the design of the CCI30 cryptocurrency index.
Estimating Treatment Effects in Mover Designs
Date: 2018-04-18 00:00:00

Researchers increasingly leverage movement across multiple treatments to
estimate causal effects. While these "mover regressions" are often motivated by
a linear constant-effects model, it is not clear what they capture under weaker
quasi-experimental assumptions. I show that binary treatment mover regressions
recover a convex average of four difference-in-difference comparisons and are
thus causally interpretable under a standard parallel trends assumption.
Estimates from multiple-treatment models, however, need not be causal without
stronger restrictions on the heterogeneity of treatment effects and
time-varying shocks. I propose a class of two-step estimators to isolate and
combine the large set of difference-in-difference quasi-experiments generated
by a mover design, identifying mover average treatment effects under
conditional-on-covariate parallel trends and effect homogeneity restrictions. I
characterize the efficient estimators in this class and derive specification
tests based on the model's overidentifying restrictions. Future drafts will
apply the theory to the Finkelstein et al. (2016) movers design, analyzing the
causal effects of geography on healthcare utilization.
Using Convex Optimization of Autocorrelation with Constrained Support and Windowing for Improved Phase Retrieval Accuracy
Date: 2018-04-16 00:00:00
Tasks: Retrieval

In imaging modalities recording diffraction data, the original image can be
reconstructed assuming known phases. When phases are unknown, oversampling and
a constraint on the support region in the original object can be used to solve
a non-convex optimization problem.
  Such schemes are ill-suited to find the optimum solution for sparse data,
since the recorded image does not correspond exactly to the original wave
function. We construct a convex optimization problem using a relaxed support
constraint and a maximum-likelihood treatment of the recorded data as a sample
from the underlying wave function. We also stress the need to use relevant
windowing techniques to account for the sampled pattern being finite.
  On simulated data, we demonstrate the benefits of our approach in terms of
visual quality and an improvement in the crystallographic R-factor from .4 to
.1 for highly noisy data.
Efficient Soft-Output Gauss-Seidel Data Detector for Massive MIMO Systems
Date: 2018-04-17 00:00:00

For massive multiple-input multiple-output (MIMO) systems, linear minimum
mean-square error (MMSE) detection has been shown to achieve near-optimal
performance but suffers from excessively high complexity due to the large-scale
matrix inversion. Being matrix inversion free, detection algorithms based on
the Gauss-Seidel (GS) method have been proved more efficient than conventional
Neumann series expansion (NSE) based ones. In this paper, an efficient GS-based
soft-output data detector for massive MIMO and a corresponding VLSI
architecture are proposed. To accelerate the convergence of the GS method, a
new initial solution is proposed. Several optimizations on the VLSI
architecture level are proposed to further reduce the processing latency and
area. Our reference implementation results on a Xilinx Virtex-7 XC7VX690T FPGA
for a 128 base-station antenna and 8 user massive MIMO system show that our
GS-based data detector achieves a throughput of 732 Mb/s with close-to-MMSE
error-rate performance. Our implementation results demonstrate that the
proposed solution has advantages over existing designs in terms of complexity
and efficiency, especially under challenging propagation conditions.
A 6.3pJ/b 30Mbps -30dB SIR-tolerant Broadband Interference-Robust Human Body Communication Transceiver using Time Domain Signal-Interference Separation
Date: 2018-04-17 00:00:00

Human Body Communication (HBC) provides a low power communication medium for
energy constrained wearable/ implantable devices in and around the human body.
This paper presents a broadband HBC transceiver implemented in 65nm CMOS that
achieves 6.3pJ/b energy efficiency at 30Mbps with -30dB interference-tolerance.
Capacitive termination at the receiver end is used to achieve a wideband HBC
channel, and Time Domain Signal-Interference Separation (TD-SIS) using
Integrating DDR (I-DDR) receiver allows a tolerance of -30 dB Signal to
Interference Ratio (SIR) with a BER <10-3. The transceiver achieves 18X
improvement in energy-efficiency compared to the State-of-the-Art HBC
transceivers while being simultaneously broadband (carrier-less, low-energy)
and interference-robust. Such order-of-magnitude improvement in
energy-efficiency and private communication through the human body may enable
applications like closed-loop neuromodulation, health-monitoring, secure
authentication among many others.
Efficient Channel Estimator with Angle-Division Multiple Access
Date: 2018-04-17 00:00:00
Tasks: Quantization

Massive multiple-input multiple-output (M-MIMO) is an enabling technology of
5G wireless communication. The performance of an M-MIMO system is highly
dependent on the speed and accuracy of obtaining the channel state information
(CSI). The computational complexity of channel estimation for an M-MIMO system
can be reduced by making use of the sparsity of the M-MIMO channel. In this
paper, we propose the hardware-efficient channel estimator based on
angle-division multiple access (ADMA) for the first time. Preamble, uplink (UL)
and downlink (DL) training are also implemented. For further
hardware-efficiency consideration, optimization regarding quantization and
approximation strategies have been discussed. Implementation techniques such as
pipelining and systolic processing are also employed for hardware regularity.
Numerical results and FPGA implementation have demonstrated the advantages of
the proposed channel estimator.
Transaction Costs in Collective Waste Recovery Systems in the EU
Date: 2018-04-18 00:00:00
Tasks: Management

The study aims to identify the institutional flaws of the current EU waste
management model by analysing the economic model of extended producer
responsibility and collective waste management systems and to create a model
for measuring the transaction costs borne by waste recovery organizations. The
model was approbated by analysing the Bulgarian collective waste management
systems that have been complying with the EU legislation for the last 10 years.
The analysis focuses on waste oils because of their economic importance and the
limited number of studies and analyses in this field as the predominant body of
research to date has mainly addressed packaging waste, mixed household waste or
discarded electrical and electronic equipment. The study aims to support the
process of establishing a circular economy in the EU, which was initiated in
2015.