pwc-archive/papers-with-abstracts huggingface dataset:
Determination of Pareto exponents in economic models driven by Markov multiplicative processes
Authors: Brendan K. Beare, Alexis Akira Toda
Date: 2017-12-05 00:00:00

This article contains new tools for studying the shape of the stationary distribution of sizes in a dynamic economic system in which units experience random multiplicative shocks and are occasionally reset. Each unit has a Markov-switching type which influences their growth rate and reset probability. We show that the size distribution has a Pareto upper tail, with exponent equal to the unique positive solution to an equation involving the spectral radius of a certain matrix-valued function. Under a non-lattice condition on growth rates, an eigenvector associated with the Pareto exponent provides the distribution of types in the upper tail of the size distribution.
Dimension Reduction for High Dimensional Vector Autoregressive Models
Authors: Gianluca Cubadda, Alain Hecq
Date: 2020-09-07 00:00:00
Tasks: Dimensionality Reduction, Vocal Bursts Intensity Prediction

This paper aims to decompose a large dimensional vector autoregessive (VAR) model into two components, the first one being generated by a small-scale VAR and the second one being a white noise sequence. Hence, a reduced number of common components generates the entire dynamics of the large system through a VAR structure. This modelling, which we label as the dimension-reducible VAR, extends the common feature approach to high dimensional systems, and it differs from the dynamic factor model in which the idiosyncratic component can also embed a dynamic pattern. We show the conditions under which this decomposition exists. We provide statistical tools to detect its presence in the data and to estimate the parameters of the underlying small-scale VAR model. Based on our methodology, we propose a novel approach to identify the shock that is responsible for most of the common variability at the business cycle frequencies. We evaluate the practical value of the proposed methods by simulations as well as by an empirical application to a large set of US economic variables.
Nonparametric inference on counterfactuals in first-price auctions
Authors: Pasha Andreyanov, Grigory Franguridi
Date: 2021-06-25 00:00:00
Tasks: counterfactual

In a classical model of the first-price sealed-bid auction with independent private values, we develop nonparametric estimators for several policy-relevant targets, such as the bidder's surplus and auctioneer's revenue under counterfactual reserve prices. Motivated by the linearity of these targets in the quantile function of bidders' values, we propose an estimator of the latter and derive its Bahadur-Kiefer expansion. This makes it possible to construct uniform confidence bands and test complex hypotheses about the auction design. Using the data on U.S. Forest Service timber auctions, we test whether setting zero reserve prices in these auctions was revenue maximizing.
Rational Pricing of Leveraged ETF Expense Ratios
Authors: Alex Garivaltis
Date: 2021-06-28 00:00:00
Tasks: Management

This paper studies the general relationship between the gearing ratio of a Leveraged ETF and its corresponding expense ratio, viz., the investment management fees that are charged for the provision of this levered financial service. It must not be possible for an investor to combine two or more LETFs in such a way that his (continuously-rebalanced) LETF portfolio can match the gearing ratio of a given, professionally managed product and, at the same time, enjoy lower weighted-average expenses than the existing LETF. Given a finite set of LETFs that exist in the marketplace, I give necessary and sufficient conditions for these products to be undominated in the price-gearing plane. In a beautiful application of the duality theorem of linear programming, I prove a kind of two-fund theorem for LETFs: given a target gearing ratio for the investor, the cheapest way to achieve it is to combine (uniquely) the two nearest undominated LETF products that bracket it on the leverage axis. This also happens to be the implementation that has the lowest annual turnover. For the writer's enjoyment, we supply a second proof of the Main Theorem on LETFs that is based on Carath\'eodory's theorem in convex geometry. Thus, say, a triple-leveraged ("UltraPro") exchange-traded product should never be mixed with cash, if the investor is able to trade in the underlying index. In terms of financial innovation, our two-fund theorem for LETFs implies that the introduction of new, undominated 2.5x products would increase the welfare of all investors whose preferred gearing ratios lie between 2x ("Ultra") and 3x ("UltraPro"). Similarly for a 1.5x product.
The Machiavellian frontier of top trading cycles
Authors: Yajing Chen, Zhenhua Jiao, Chenfeng Zhang, Luosai Zhang
Date: 2021-06-28 00:00:00

This paper studies the housing market problem introduced by Shapley and Scarf (1974). We probe the Machiavellian frontier of the well-known top trading cycles (TTC) rule by weakening strategy-proofness and providing new characterizations for this rule. Specifically, our contribution lies in three aspects. First, we weaken the concept of strategy-proofness and introduce a new incentive notion called truncation-invariance, where the truthful preference-reporting assignment cannot be altered by any agent through misreporting a truncation of the true preference at the assignment produced by the true preference unilaterally. Second, we characterize the TTC rule by the following three groups of axioms: individual rationality, pair-efficiency, truncation-invariance; individual rationality, Pareto efficiency, truncation-invariance; individual rationality, endowments-swapping-proofness, truncation-invariance.1 The new characterizations refine several previous results.2 Third, we show through examples that the characterization results of Takamiya (2001) and Miyagawa (2002) can no longer be obtained if strategy-proofness is replaced with truncation-invariance.
Mobile Microphone Array Speech Detection and Localization in Diverse Everyday Environments
Authors: Pasi Pertilä, Emre Cakir, Aapo Hakala, Eemi Fagerlund, Tuomas Virtanen, Archontis Politis, Antti Eronen
Date: 2021-06-28 00:00:00
Tasks: Sound Event Localization and Detection

Joint sound event localization and detection (SELD) is an integral part of developing context awareness into communication interfaces of mobile robots, smartphones, and home assistants. For example, an automatic audio focus for video capture on a mobile phone requires robust detection of relevant acoustic events around the device and their direction. Existing SELD approaches have been evaluated using material produced in controlled indoor environments, or the audio is simulated by mixing isolated sounds to different spatial locations. This paper studies SELD of speech in diverse everyday environments, where the audio corresponds to typical usage scenarios of handheld mobile devices. In order to allow weighting the relative importance of localization vs. detection, we will propose a two-stage hierarchical system, where the first stage is to detect the target events, and the second stage is to localize them. The proposed method utilizes convolutional recurrent neural network (CRNN) and is evaluated on a database of manually annotated microphone array recordings from various acoustic conditions. The array is embedded in a contemporary mobile phone form factor. The obtained results show good speech detection and localization accuracy of the proposed method in contrast to a non-hierarchical flat classification model.
Versatile Video Coding Standard: A Review from Coding Tools to Consumers Deployment
Authors: Wassim Hamidouche, Thibaud Biatek, Mohsen Abdoli, Edouard François, Fernando Pescador, Miloš Radosavljević, Daniel Menard, Mickael Raulet
Date: 2021-06-27 00:00:00

The amount of video content and the number of applications based on multimedia information increase each day. The development of new video coding standards is a challenge to increase the compression rate and other important features with a reasonable increase in the computational load. Video Experts Team (JVET) of ITU-T and the JCT group within ISO/IEC have worked together to standardize the Versatile Video Coding, approved finally in July 2020 as ITU-T H.266 | MPEG-I - Part 3 (ISO/IEC 23090-3) standard. This paper overviews some interesting consumer electronic use cases, the compression tools described in the standard, the current available real time implementations and the first industrial trials done with this standard.
Gaussian Process Regression for Active Sensing Probabilistic Structural Health Monitoring: Experimental Assessment Across Multiple Damage and Loading Scenarios
Authors: Ahmad Amer, Fotis Kopsaftopoulos
Date: 2021-06-28 00:00:00
Tasks: Decision Making, Management, Structural Health Monitoring

In the near future, Structural Health Monitoring (SHM) technologies will be capable of overcoming the drawbacks in the current maintenance and life-cycle management paradigms, namely: cost, increased downtime, less-than-optimal safety management paradigm and the limited applicability of fully-autonomous operations. In the context of SHM, one of the most challenging tasks is damage quantification. Current methods face accuracy and/or robustness issues when it comes to varying operating and environmental conditions. In addition, the damage/no-damage paradigm of current frameworks does not offer much information to maintainers on the ground for proper decision-making. In this study, a novel structural damage quantification framework is proposed based on widely-used Damage Indices (DIs) and Gaussian Process Regression Models (GPRMs). The novelty lies in calculating the probability of an incoming test DI point originating from a specific state, which allows for probability-educated decision-making. This framework is applied to three test cases: a Carbon Fiber-Reinforced Plastic (CFRP) coupon with attached weights as simulated damage, an aluminum coupon with a notch, and an aluminum coupon with attached weights as simulated damage under varying loading states. The state prediction method presented herein is applied to single-state quantification in the first two test cases, as well as the third one assuming the loading state is known. Finally, the proposed method is applied to the third test case assuming neither the damage size nor the load is known in order to predict both simultaneously from incoming DI test points. In applying this framework, two forms of GPRMs (standard and variational heteroscedastic) are used in order to critically assess their performances with respect to the three test cases.
Channel Estimation for RIS-Aided Multiuser Millimeter-Wave Systems
Authors: Gui Zhou, Cunhua Pan, Hong Ren, Petar Popovski, A. Lee Swindlehurst
Date: 2021-06-28 00:00:00

Channel estimation in the RIS-aided massive multiuser multiple-input single-output (MU-MISO) wireless communication systems is challenging due to the passive feature of RIS and the large number of reflecting elements that incur high channel estimation overhead. To address this issue, we propose a novel cascaded channel estimation strategy with low pilot overhead by exploiting the sparsity and the correlation of multiuser cascaded channels in millimeter-wave massive MISO systems. Based on the fact that the phsical positions of the BS, the RIS and users may not change in several or even tens of consecutive channel coherence blocks, we first estimate the full channel state information (CSI) including all the angle and gain information in the first coherence block, and then only re-estimate the channel gains in the remaining coherence blocks with much less pilot overhead. In the first coherence block, we propose a two-phase channel estimation method, in which the cascaded channel of one typical user is estimated in Phase I based on the linear correlation among cascaded paths, while the cascaded channels of other users are estimated in Phase II by utilizing the partial CSI of the common base station (BS)-RIS channel obtained in Phase I. The total theoretical minimum pilot overhead in the first coherence block is $8J-2+(K-1)\left\lceil (8J-2)/L\right\rceil $, where $K$, $L$ and $J$ denote the numbers of users, paths in the BS-RIS channel and paths in the RIS-user channel, respectively. In each of the remaining coherence blocks, the minimum pilot overhead is $JK$. Moreover, the training phase shift matrices at the RIS are optimized to improve the estimation performance.
Mixed-Spectrum Signals -- Discrete Approximations and Variance Expressions for Covariance Estimates
Authors: Filip Elvander, Johan Karlsson
Date: 2021-06-28 00:00:00
Tasks: Direction of Arrival Estimation

The estimation of the covariance function of a stochastic process, or signal, is of integral importance for a multitude of signal processing applications. In this work, we derive closed-form expressions for the variance of covariance estimates for mixed-spectrum signals, i.e., spectra containing both absolutely continuous and singular parts. The results cover both finite-sample and asymptotic regimes, allowing for assessing the exact speed of convergence of estimates to their expectations, as well as their limiting behavior. As is shown, such covariance estimates may converge even for non-ergodic processes. Furthermore, we consider approximating signals with arbitrary spectral densities by sequences of singular spectrum, i.e., sinusoidal, processes, and derive the limiting behavior of covariance estimates as both the sample size and the number of sinusoidal components tend to infinity. We show that the asymptotic regime variance can be described by a time-frequency resolution product, with dramatically different behavior depending on how the sinusoidal approximation is constructed. In a few numerical examples we illustrate the theory and the corresponding implications for direction of arrival estimation.
FRaC: FMCW-Based Joint Radar-Communications System via Index Modulation
Authors: Dingyou Ma, Nir Shlezinger, Tianyao Huang, Yimin Liu, Yonina C. Eldar
Date: 2021-06-28 00:00:00
Tasks: Autonomous Vehicles

Dual function radar communications (DFRC) systems are attractive technologies for autonomous vehicles, which utilize electromagnetic waves to constantly sense the environment while simultaneously communicating with neighbouring devices. An emerging approach to implement DFRC systems is to embed information in radar waveforms via index modulation (IM). Implementation of DFRC schemes in vehicular systems gives rise to strict constraints in terms of cost, power efficiency, and hardware complexity. In this paper, we extend IM-based DFRC systems to utilize sparse arrays and frequency modulated continuous waveforms (FMCWs), which are popular in automotive radar for their simplicity and low hardware complexity. The proposed FMCW-based radar-communications system (FRaC) operates at reduced cost and complexity by transmitting with a reduced number of radio frequency modules, combined with narrowband FMCW signalling. This is achieved via array sparsification in transmission, formulating a virtual multiple-input multiple-output array by combining the signals in one coherent processing interval, in which the narrowband waveforms are transmitted in a randomized manner. Performance analysis and numerical results show that the proposed radar scheme achieves similar resolution performance compared with a wideband radar system operating with a large receive aperture, while requiring less hardware overhead. For the communications subsystem, FRaC achieves higher rates and improved error rates compared to dual-function signalling based on conventional phase modulation.
Learning to Sample: Data-Driven Sampling and Reconstruction of FRI Signals
Authors: Satish Mulleti, Haiyang Zhang, Yonina C. Eldar
Date: 2021-06-28 00:00:00
Tasks: compressed sensing

Finite-rate-of-innovation (FRI) signals are ubiquitous in applications such as radar, ultrasound, and time of flight imaging. Due to their finite degrees of freedom, FRI signals can be sampled at sub-Nyquist rates using appropriate sampling kernels and reconstructed using sparse-recovery algorithms. Typically, Fourier samples of the FRI signals are used for reconstruction. The reconstruction quality depends on the choice of Fourier samples and recovery method. In this paper, we consider to jointly optimize the choice of Fourier samples and reconstruction parameters. Our framework is a combination of a greedy subsampling algorithm and a learning-based sparse recovery method. Unlike existing techniques, the proposed algorithm can flexibly handle changes in the sampling rate and does not suffer from differentiability issues during training. Importantly, exact knowledge of the FRI pulse is not required. Numerical results show that, for a given number of samples, the proposed joint design leads to lower reconstruction error for FRI signals compared to independent data-driven design methods for both noisy and clean samples. Our learning to sample approach can be readily applied to other sampling setups as well including compressed sensing problems.
Outage Performance Analysis of Widely Linear Receivers in Uplink Multi-user MIMO Systems
Authors: Ronghua Gui, Naveen Mysore Balasubramanya, Lutz Lampe
Date: 2021-06-27 00:00:00
Tasks: Diversity

This paper considers the application of widely linear (WL) receivers in an uplink multi-user system using real-valued modulation schemes, where the cellular base station (BS) with multiple antennas provides connectivity for randomly deployed single-antenna users. The targeted use case is massive machine type communication (mMTC) with grant-free access in the uplink, where the network is required to host a large number of low data rate devices transmitting in an uncoordinated fashion. Four types of WL receivers are investigated, namely the WL zero-forcing (ZF) and the WL minimum meansquared error (MMSE) receivers, along with their enhanced versions employing successive interference cancellation (SIC) with channel-dependent ordering, i.e., the WL-ZF-SIC and WL-MMSE-SIC receivers. The outage performances of these receivers are analytically characterized in the high signal-to-noise ratio (SNR) regime and compared to those of conventional linear (CL) receivers using complex-valued modulation schemes. For the non-SIC receivers, we show that, when compared to the CL counterparts, the WL receivers yield a higher diversity gain when decoding the same number of users and have the same diversity gain but a decreased coding gain when the number of users is nearly doubled. The outage performance analysis of WL-SIC receivers is facilitated by the marginal distribution of ordered eigenvalues of a real-valued Wishart matrix. It is shown that the SIC operation with channel-dependent ordering brings no additional diversity gain to the WL receivers but instead increases the coding gain. Moreover, the coding gain of WL-SIC receivers grows as the number of users increases and even exceeds that of CL-SIC receivers under suitable conditions.
Second-Order Perturbation Theory-Based Digital Predistortion for Fiber Nonlinearity Compensation
Authors: O. S. Sunish Kumar, A. Amari, O. A. Dobre, R. Venkatesan
Date: 2021-06-27 00:00:00

The first-order (FO) perturbation theory-based nonlinearity compensation (PB-NLC) technique has been widely investigated to combat the detrimental effects of the intra-channel Kerr nonlinearity in polarization-multiplexed (Pol-Mux) optical fiber communication systems. However, the NLC performance of the FO-PB-NLC technique is significantly limited in highly nonlinear regimes of the Pol-Mux long-haul optical transmission systems. In this paper, we extend the FO theory to second-order (SO) to improve the NLC performance. This technique is referred to as the SO-PB-NLC. A detailed theoretical analysis is performed to derive the SO perturbative field for a Pol-Mux optical transmission system. Following that, we investigate a few simplifying assumptions to reduce the implementation complexity of the SO-PB-NLC technique. The numerical simulations for a single-channel system show that the SO-PB-NLC technique provides an improved bit-error-rate performance and increases the transmission reach, in comparison with the FO-PB-NLC technique. The complexity analysis demonstrates that the proposed SO-PB-NLC technique has a reduced computational complexity when compared to the digital back-propagation with one step per span.
A Joint Technique for Nonlinearity Compensation in CO-OFDM Superchannel Systems
Authors: O. S. Sunish Kumar, A. Amari, O. A. Dobre, R. Venkatesan, S. K. Wilson
Date: 2021-06-27 00:00:00

We propose a technique combining the singlechannel digital-back-propagation (SC-DBP) with phaseconjugated-twin-wave (PCTW) to compensate nonlinearities in CO-OFDM superchannel systems. This exhibits a similar performance as multi-channel DBP while providing increased transmission reach compared to SC-DBP, PCTW, and linear dispersion compensation (LDC).
A Spectrally Efficient Linear Polarization Coding Scheme for Fiber Nonlinearity Compensation in CO-OFDM Systems
Authors: O. S. Sunish Kumar, O. A. Dobre, R. Venkatesan, S. K. Wilson, O. Omomukuyo, A. Amari, D. Chang
Date: 2021-06-27 00:00:00

In this paper, we propose a linear polarization coding scheme (LPC) combined with the phase conjugated twin signals (PCTS) technique, referred to as LPC-PCTS, for fiber nonlinearity mitigation in coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. The LPC linearly combines the data symbols on the adjacent subcarriers of the OFDM symbol, one at full amplitude and the other at half amplitude. The linearly coded data is then transmitted as phase conjugate pairs on the same subcarriers of the two OFDM symbols on the two orthogonal polarizations. The nonlinear distortions added to these subcarriers are essentially anti-correlated, since they carry phase conjugate pairs of data. At the receiver, the coherent superposition of the information symbols received on these pairs of subcarriers eventually leads to the cancellation of the nonlinear distortions. We conducted numerical simulation of a single channel 200 Gb/s CO-OFDM system employing the LPCPCTS technique. The results show that a Q-factor improvement of 2.3 dB and 1.7 dB with and without the dispersion symmetry, respectively, when compared to the recently proposed phase conjugated subcarrier coding (PCSC) technique, at an average launch power of 3 dBm. In addition, our proposed LPCPCTS technique shows a significant performance improvement when compared to the 16-quadrature amplitude modulation (QAM) with phase conjugated twin waves (PCTW) scheme, at the same spectral efficiency, for an uncompensated transmission distance of 2800 km.
Simple Wideband RCS Reduction by Phase Gradient Modulated Surface
Authors: Yousef Azizi, Mohammad Soleimani, Seyed Hasan Sedighi, Ladislau Matekovits
Date: 2021-06-27 00:00:00

This paper presents the design and implementation of a simple, single-layer, broadband (97%, 11.3-32.3 GHz) Radar Cross Section Reduction (RCSR) Modulated Surface (MS). It uses modulation of the edge-length of the square patch (SP) radiators within adjacent unit cells. By using Sinusoidal Modulation (SM) of the edge length of the unit cells, the unit cells sequences with phase gradient, that plays an effective role in improving the RCSR, can be used for wideband RCSR achievement. The proposed structure with the dimension of 250*250mm2 that consists of 40 * 40 unit cells with period of 6mm printed on a RO4003 substrate of 1.6mm thickness and has been considered. Measurements on a prototype were conducted considering both mono- and bi-static arrangements for oblique incidences for both TM and TE polarization tests. A good agreement between simulation and measurement results proves the validity of the design criteria.