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We consider a robust and self-reliant (or "egoistic") variation of the rigid body localization (RBL) problem, in which a primary rigid body seeks to estimate the pose (i.e., location and orientation) of another rigid body (or "target"), relative to its own, without the assistance of external infrastructure, without prior knowledge of the shape of the target, and taking into account the possibility that the available observations are incomplete. Three complementary contributions are then offered for such a scenario. The first is a method to estimate the translation vector between the center point of both rigid bodies, which unlike existing techniques does not require that both objects have the same shape or even the same number of landmark points. This technique is shown to significantly outperform the state-of-the-art (SotA) under complete information, but to be sensitive to data erasures, even when enhanced by matrix completion methods. The second contribution, designed to offer improved performance in the presence of incomplete information, offers a robust alternative to the latter, at the expense of a slight relative loss under complete information. Finally, the third contribution is a scheme for the estimation of the rotation matrix describing the relative orientation of the target rigid body with respect to the primary. Comparisons of the proposed schemes and SotA techniques demonstrate the advantage of the contributed methods in terms of root mean square error (RMSE) performance under fully complete information and incomplete conditions.

Introduced with the advent of statistical wireless channel models for high mobility communications and having a profound role in communication-centric (CC) integrated sensing and communications (ISAC), the doubly-dispersive (DD) channel structure has long been heralded as a useful tool enabling the capture of the most important fading effects undergone by an arbitrary time-domain transmit signal propagating through some medium. However, the incorporation of this model into multiple-input multiple-output (MIMO) system setups, relying on the recent paradigm-shifting transceiver architecture based on stacked intelligent metasurfaces (SIM), in an environment with reconfigurable intelligent surfaces (RISs) remains an open problem due to the many intricate details that have to be accounted for. In this paper, we fill this gap by introducing a novel DD MIMO channel model that incorporates an arbitrary number of RISs in the ambient, as well as SIMs equipping both the transmitter and receiver. We then discuss how the proposed metasurfaces-parametrized DD (MPDD) channel model can be seamlessly applied to waveforms that are known to perform well in DD environments, namely, orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), and affine frequency division multiplexing (AFDM), with each having their own inherent advantages and disadvantages. An illustrative application of the programmable functionality of the proposed model is finally presented to showcase its potential for boosting the performance of the aforementioned waveforms. Our numerical results indicate that the design of waveforms suitable to mitigating the effects of DD channels is significantly impacted by the emerging SIM technology., Comment: Submitted to an IEEE journal for possible publication

We propose a novel message-passing solution to the sixth-dimensional (6D) moving rigid body localization (RBL) problem, in which the three-dimensional (3D) translation vector and rotation angles, as well as their corresponding translational and angular velocities, are all estimated by only utilizing the relative range and Doppler measurements between the "anchor" sensors located at an 3D (rigid body) observer and the "target" sensors of another rigid body. The proposed method is based on a bilinear Gaussian belief propagation (GaBP) framework, employed to estimate the absolute sensor positions and velocities using a range- and Doppler-based received signal model, which is then utilized in the reconstruction of the RBL transformation model, linearized under a small-angle approximation. The method further incorporates a second bivariate GaBP designed to directly estimate the 3D rotation angles and translation vectors, including an interference cancellation (IC) refinement stage to improve the angle estimation performance, followed by the estimation of the angular and the translational velocities. The effectiveness of the proposed method is verified via simulations, which confirms its improved performance compared to equivalent state-of-the-art (SotA) techniques., Comment: arXiv admin note: text overlap with arXiv:2407.09232

We propose a novel flexible and scalable framework to design integrated communication and computing (ICC) -- a.k.a. over-the-air computing (AirComp)-- receivers. To elaborate, while related literature so far has generally focused either on theoretical aspects of ICC or on the design of beamforming (BF) algorithms for AirComp, we propose a framework to design receivers capable of simultaneously detecting communication symbols and extracting the output of the AirComp operation, in a manner that can: a) be systematically generalized to any nomographic function, b) scaled to a massive number of user equipments (UEs) and edge devices (EDs), and c) support the multiple computation streams. For the sake of illustration, we demonstrate the proposed method under a setting consisting of the uplink from multiple single-antenna UEs/EDs simultaneously transmitting communication and computing signals to a single multiple-antenna base station (BS)/access point (AP). The receiver, which seeks to detect all communication symbols and minimize the distortion over the computing signals, requires that only a fraction of the transmit power be allocated to the latter, therefore coming close to the ideal (but unattainable) condition that computing is achieved "for free", without taking resources from the communication system. The design leverages the Gaussian belief propagation (GaBP) framework relying only on element-wise scalar operations, which allows for its use in massive settings, as demonstrated by simulation results incorporating up to 200 antennas and 200 UEs/EDs. They also demonstrate the efficacy of the proposed method under all various loading conditions, with the performance of the scheme approaching fundamental limiting bounds in the under/fully loaded cases., Comment: Submitted to the IEEE for possible publication

We demonstrate that the search space of the quadratic assignment problem (QAP), known as an NP-hard combinatorial optimization problem, can be reduced using Grover adaptive search (GAS) with Dicke state operators. To that end, we first revise the traditional quadratic formulation of the QAP into a higher-order formulation, introducing a binary encoding method ordered by a descending Hamming weight, such that the number of terms in the objective function is reduced. We also show that the phase gate in the GAS can be replaced by a rotation gate about the Z axis, simplifying the quantum circuit without any penalty. Algebraic analyses in terms of the number of qubits, quantum gates, and query complexity are performed, which indicate that our proposed approach significantly reduces the search space size, improving convergence performance to the optimal solution compared to the conventional one. Interestingly, it is suggested that the higher-order formulation is effective for problems whose size are powers of two, while the quadratic formulation is more effective for other sizes, indicating that switching between the two formulations can enhance the feasibility of the GAS-solved QAP., Comment: 12 pages, 6 figures

In this paper, we propose a novel low complexity time domain (TD) oversampling receiver framework under affine frequency division multiplexing (AFDM) waveforms for joint channel estimation and data detection (JCEDD). Leveraging a generalized doubly-dispersive channel model, we first derive the input-output (I/O) relationship for arbitrary waveforms when oversampled in the TD and present the I/O relationship for AFDM as an example. Subsequently, utilizing the multiple sample streams created via the oversampling procedure, we use the parametric bilinear Gaussian belief propagation (PBiGaBP) technique to conduct JCEDD for decoding the transmitted data and estimating the complex channel coefficients. Simulation results verify significant performance improvements both in terms of data decoding and complex channel coefficient estimation with improved robustness against a varying number of pilots over a conventional Nyquist sampling rate receiver., Comment: Submitted to the IEEE for possible publication

We consider the peak-to-average power ratio (PAPR) reduction challenge of orthogonal frequency division multiplexing (OFDM) systems utilizing tone reservation (TR) under a sensing-enabling constraint, such that the signals placed in the reserved tones (RTs) can be exploited for Integrated Sensing and Communication (ISAC). To that end, the problem is first cast as an unconstrained manifold optimization problem, and then solved via an iterative projected gradient descent algorithm assisted by an approximation of the infinity norm. Simulation results show that the proposed method, while maintaining a level of PAPR reduction similar to state of the art (SotA), not only has lower computational complexity but also outperforms the alternatives in terms of sensing performance.

We propose a quantum-assisted solution for the maximum likelihood detection (MLD) of generalized spatial modulation (GSM) signals. Specifically, the MLD of GSM is first formulated as a novel polynomial optimization problem, followed by the application of a quantum algorithm, namely, the Grover adaptive search. The performance in terms of query complexity of the proposed method is evaluated and compared to the classical alternative via a numerical analysis, which reveals that under fault-tolerant quantum computation, the proposed method outperforms the classical solution if the number of data symbols and the constellation size are relatively large., Comment: 5 pages, 4 figures, accepted for presentation at the IEEE 100th Vehicular Technology Conference (VTC2024-Fall)

Vehicle-to-everything (V2X) perception describes a suite of technologies used to enable vehicles to perceive their surroundings and communicate with various entities, such as other road users, infrastructure, or the network/cloud. With the development of autonomous driving, V2X perception is becoming increasingly relevant, as can be seen by the tremendous attention recently given to integrated sensing and communication (ISAC) technologies. In this context, rigid body localization (RBL) also emerges as one important technology which enables the estimation of not only target's positions, but also their shape and orientation. This article discusses the need for RBL, its benefits and opportunities, challenges and research directions, as well as its role in the standardization of the sixth-generation (6G) and beyond fifth generation (B5G) applications.

We propose a novel solution to the rigid body localization (RBL) problem, in which the three-dimensional (3D) rotation and translation is estimated by only utilizing the range measurements between the wireless sensors on the rigid body and the anchor sensors. The proposed framework first constructs a linear Gaussian belief propagation (GaBP) algorithm to estimate the absolute sensor positions utilizing the range-based received signal model, which is used for the reconstruction of the RBL transformation model, linearized with a small-angle approximation. In light of the reformulated system, a second bivariate GaBP is designed to directly estimate the 3D rotation angles and translation distances, with an interference cancellation (IC) refinement to improve the angle estimation performance. The effectiveness of the proposed method is verified via numerical simulations, highlighting the superior performance of the proposed method against the state-of-the-art (SotA) techniques for the position, rotation, and translation estimation performance.

Integrated sensing and communications (ISAC) and index modulation (IM) are promising technologies for beyond fifth generation (B5G) and sixth generation (6G) systems. While ISAC enables new applications, IM is attractive for its inherent energy and spectral efficiencies. In this article we propose massive IM as an enabler of ISAC, by considering transmit signals with information conveyed through the indexation of the resources utilized in their transmission, and pilot symbols exploited for sensing. In order to overcome the complexity hurdle arising from the large sizes of IM codebooks, we propose a novel message passing (MP) decoder designed under the Gaussian belief propagation (GaBP) framework exploiting a novel unit vector decomposition (UVD) of IM signals with purpose-derived novel probability distributions. The proposed method enjoys a low decoding complexity that is independent of combinatorial factors, while still approaching the performance of unfeasible state-of-the-art (SotA) search-based methods. The effectiveness of the proposed approach is demonstrated via complexity analysis and numerical results for piloted generalized quadrature spatial modulation (GQSM) systems of large sizes (up to 96 antennas).

The journal Energy Economics, a leading international peer-reviewed outlet for economic theory in the energy sector, celebrates its 45th anniversary in 2024. This article uses a bibliometric approach to present a retrospective of the journal's contributions. The study includes all publications from the journal based on data from the Web of Science and Scopus databases. The resulting sample comprises 6,563 documents covering the period from 1979 to April 2024. The annual publication rate increased by 1.02 percent, with an average of 40.07 citations per document. Institutions from the United States of America and China lead in the number of articles published in the journal. A co-occurrence analysis of keywords was conducted, complemented by a sub-sample analysis, to provide a detailed view of thematic development and evolution over time. Finally, the article highlights future thematic trends of the journal, offering insights for editorial guidelines and interested authors., Comment: Bibliometric Analysis

We propose a novel method for blind bistatic radar parameter estimation (RPE), which enables integrated sensing and communications (ISAC) by allowing passive (receive) base stations (BSs) to extract radar parameters (ranges and velocities of targets), without requiring knowledge of the information sent by an active (transmit) BS to its users. The contributed method is formulated with basis on the covariance of received signals, and under a generalized doubly-dispersive channel model compatible with most of the waveforms typically considered for ISAC, such as orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS) and affine frequency division multiplexing (AFDM). The original non-convex problem, which includes an $\ell_0$-norm regularization term in order to mitigate clutter, is solved not by relaxation to an $\ell_1$-norm, but by introducing an arbitrarily-tight approximation then relaxed via fractional programming (FP). Simulation results show that the performance of the proposed method approaches that of an ideal system with perfect knowledge of the transmit signal covariance with an increasing number of transmit frames., Comment: Submitted to the IEEE for possible publication

We propose new formulations of max-sum and max-min dispersion problems that enable solutions via the Grover adaptive search (GAS) quantum algorithm, offering quadratic speedup. Dispersion problems are combinatorial optimization problems classified as NP-hard, which appear often in coding theory and wireless communications applications involving optimal codebook design. In turn, GAS is a quantum exhaustive search algorithm that can be used to implement full-fledged maximum-likelihood optimal solutions. In conventional naive formulations however, it is typical to rely on a binary vector spaces, resulting in search space sizes prohibitive even for GAS. To circumvent this challenge, we instead formulate the search of optimal dispersion problem over Dicke states, an equal superposition of binary vectors with equal Hamming weights, which significantly reduces the search space leading to a simplification of the quantum circuit via the elimination of penalty terms. Additionally, we propose a method to replace distance coefficients with their ranks, contributing to the reduction of the number of qubits. Our analysis demonstrates that as a result of the proposed techniques a reduction in query complexity compared to the conventional GAS using Hadamard transform is achieved, enhancing the feasibility of the quantum-based solution of the dispersion problem., Comment: 13 pages, 7 figures

We propose new schemes for joint channel and data estimation (JCDE) and radar parameter estimation (RPE) in doubly-dispersive channels, such that integrated sensing and communications (ISAC) is enabled by user equipment (UE) independently performing JCDE, and base stations (BSs) performing RPE. The contributed JCDE and RPE schemes are designed for waveforms known to perform well in doubly-dispersive channels, under a unified model that captures the features of either legacy orthogonal frequency division multiplexing (OFDM), state-of-the-art (SotA) orthogonal time frequency space (OTFS), and next-generation affine frequency division multiplexing (AFDM) systems. The proposed JCDE algorithm is based on a Bayesian parametric bilinear Gaussian belief propagation (PBiGaBP) framework first proposed for OTFS and here shown to apply to all aforementioned waveforms, while the RPE scheme is based on a new probabilistic data association (PDA) approach incorporating a Bernoulli-Gaussian denoising, optimized via expectation maximization (EM). Simulation results demonstrate that JCDE in AFDM systems utilizing a single pilot per block significantly outperforms the SotA alternative even if the latter is granted a substantial power advantage. Similarly, the AFDM-based RPE scheme is found to outperform the OTFS-based approach, as well as the sparse Bayesian learning (SBL) technique, regardless of the waveform used., Comment: Submitted to IEEE for possible publication

We consider the problem of peak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM) systems via optimized sparsification of tone reservation (TR). In particular, we propose a novel TR optimization method in which the minimum number of effectively used peak-reserved tones (PRTs) required to satisfy a prescribed PAPR level is found, leaving the remaining PRTs free to be opportunistically utilized by other functionalities, such as joint communication and sensing (JCAS), index modulation (IM), cognitive radio (CR) and others. The proposed method relies on an l0 norm regularization approach to penalize the number of PRTs, leading to a problem convexized via fractional programming (FP), whose solution is shown to ensure that the prescribed PAPR is achieved with high probability with a smaller number of PRTs than state of the art (SotA) methods. The contribution can be seen as a mechanism to enable the opportunistic integration of adjacent functionalities into existing OFDM-based systems.

We consider a novel algorithm, for the completion of partially observed low-rank matrices in a structured setting where each entry can be chosen from a finite discrete alphabet set, such as in common recommender systems. The proposed low-rank matrix completion (MC) method is an improved variation of state-of-the-art (SotA) discrete aware matrix completion method which we previously proposed, in which discreteness is enforced by an $\ell_0$-norm regularizer, not by replaced with the $\ell_1$-norm, but instead approximated by a continuous and differentiable function normalized via fractional programming (FP) under a proximal gradient (PG) framework. Simulation results demonstrate the superior performance of the new method compared to the SotA techniques as well as the earlier $\ell_1$-norm-based discrete-aware matrix completion approach., Comment: Accepted at the IEEE 2024 Asilomar Conference on Signals, Systems, and Computers

We describe a novel index modulation (IM) scheme exploiting a unique feature of the recently proposed affine frequency division multiplexing (AFDM) in doubly-dispersive (DD) channels. Dubbed AFDM chirp-permutation-index modulation (CPIM), the proposed method encodes additional information via the permutation of the discrete affine Fourier Transform (DAFT) chirp sequence, without any sacrifice of the various beneficial properties of the AFDM waveform in DD channels. The effectiveness of the proposed method is validated via simulation results leveraging a novel reduced-complexity minimum mean-squared-error (MMSE)-based maximum-likelihood (ML) detector, highlighting the gains over the classical AFDM. As part of the work two interesting problems related to optimizing AFDM-CPIM are identified: the optimal codebook design problem, over a discrete solution space of dimension $\binom{N!}{K}$, where $N$ is the number of subcarriers and $K$ is the number of codewords; and the ML detection problem whose solution space is of dimension $KM^N$, where $M$ is the constellation size. In order to alleviate the computational complexity of these problems and enable large-scale variations of AFDM-CPIM, the two problems are reformulated as a higher-order binary optimization problem and mapped to the well-known quantum Grover adaptive search (GAS) algorithm for their solution.

We consider the estimation of three-dimensional (3D) radar parameters, namely, bearing or angle-of-arrival (AoA), delay or range, and Doppler shift velocity, under a mono-static multiple-input multiple-output (MIMO) joint communications and radar (JCR) system based on Orthogonal Time Frequency Space (OTFS) signals. In particular, we propose a novel two-step algorithm to estimate the three radar parameters sequentially, where the AoA is obtained first, followed by the estimation of range and velocity via a reduced two-dimensional (2D) grid maximum likelihood (ML) search in the delay-Doppler (DD) domain. Besides the resulting lower complexity, the decoupling of AoA and DD estimation enables the incorporation of an linear minimum mean square error (LMMSE) procedure in the ML estimation of range and velocity, which are found to significantly outperform State-of-the-Art (SotA) alternatives and approach the fundamental limits of the Cram`er-Rao lower bound (CRLB) and search grid resolution., Comment: Accepted at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, 14~19 April 2024

The expected shortage of Li due to the strong increase in electromobility is an important issue for the recovery of Li from spent Li-ion batteries. One approach is pyrometallurgical processing, during which ignoble elements such as Li, Al and Mn enter the slag system. The Engineered Artificial Minerals (EnAM) strategy aims to efficiently recover critical elements. This study focuses on stabilizing Li-manganates in a synthetic slag and investigates the relationship between Mn4+ and Mg and Al in relation to phase formation. Therefore, three synthetic slags (Li, Mg, Al, Si, Ca, Mn, O) were synthesized. In addition to LiMn3+O2, Li2Mn4+O3 was also stabilized. Both phases crystallized in a Ca-silicate-rich matrix. In the structure of Li2MnO3 and LiMnO2, Li and Mn can substitute each other in certain proportions. As long as a mix of Mn2+ and Mn3+ is present in the slag, spinels form through the addition of Mg and/or Al.

Next-generation wireless systems will offer integrated sensing and communications (ISAC) functionalities not only in order to enable new applications, but also as a means to mitigate challenges such as doubly-dispersive channels, which arise in high mobility scenarios and/or at millimeter-wave (mmWave) and Terahertz (THz) bands. An emerging approach to accomplish these goals is the design of new waveforms, which draw from the inherent relationship between the doubly-dispersive nature of time-variant (TV) channels and the environmental features of scatterers manifested in the form of multi-path delays and Doppler shifts. Examples of such waveforms are the delay-Doppler domain orthogonal time frequency space (OTFS) and the recently proposed chirp domain affine frequency division multiplexing (AFDM), both of which seek to simultaneously combat the detrimental effects of double selectivity and exploit them for the estimation (or sensing) of environmental information. This article aims to provide a consolidated and comprehensive overview of the signal processing techniques required to support reliable ISAC over doubly-dispersive channels in beyond fifth generation (B5G)/sixth generation (6G) systems, with an emphasis on OTFS and AFDM waveforms, as those, together with the traditional orthogonal frequency division multiplexing (OFDM) waveform, suffice to elaborate on the most relevant properties of the trend. The analysis shows that OTFS and AFDM indeed enable significantly improved robustness against inter-carrier interference (ICI) arising from Doppler shifts compared to OFDM. In addition, the inherent delay-Doppler domain orthogonality of the OTFS and AFDM effective channels is found to provide significant advantages for the design and the performance of integrated sensing functionalities., Comment: Please find the official IEEE published version of this article on IEEE Xplore here (https://ieeexplore.ieee.org/abstract/document/10769778), and cite the full article

Generalized quadrature spatial modulation (GQSM) schemes are known to achieve high energy- and spectral- efficiencies by modulating information both in transmitted symbols and in coded combinatorial activations of subsets of multiple transmit antennas. A challenge of the approach is, however, the decoding complexity which scales with the efficiency of the scheme. In order to circumvent this bottleneck and enable high-performance and feasible GQSM in massive multiple-input multiple-output (mMIMO) scenarios, we propose a novel decoding algorithm which enjoys a complexity order that is independent of the combinatorial factor. This remarkable feature of the proposed decoder is a consequence of a novel vectorized Gaussian belief propagation (GaBP) algorithm, here contributed, whose message passing (MP) rules leverage both pilot symbols and the unit vector decomposition (UVD) of the GQSM signal structure. The effectiveness of the proposed UVD-GaBP method is illustrated via computer simulations including numerical results for systems of a size never before reported in related literature (up to 32 transmit antennas), which demonstrates the potential of the approach in paving the way towards high energy and spectral efficiency for wireless systems in a truly mMIMO setting.

This white paper describes a proposed article that will aim to provide a thorough study of the evolution of the typical paradigm of wireless localization (WL), which is based on a single point model of each target, towards wireless rigid body localization (W-RBL). We also look beyond the concept of RBL itself, whereby each target is modeled as an independent multi-point three-dimensional (3D), with shape enforced via a set of conformation constraints, as a step towards a more general approach we refer to as soft-connected RBL, whereby an ensemble of several objects embedded in a given environment, is modeled as a set of soft-connected 3D objects, with rigid and soft conformation constraints enforced within each object and among them, respectively. A first intended contribution of the full version of this article is a compact but comprehensive survey on mechanisms to evolve WL algorithms in W-RBL schemes, considering their peculiarities in terms of the type of information, mathematical approach, and features the build on or offer. A subsequent contribution is a discussion of mechanisms to extend W-RBL techniques to soft-connected rigid body localization (SCW-RBL) algorithms.

**PLEASE FIND THE FULL EXTENDED ARTICLE "From OTFS to AFDM: A Comparative Study of Next-Generation Waveforms for ISAC in Doubly-Dispersive Channels" (Accepted for publication at the IEEE Signal Processing Magazine - Special Issue on Signal Processing for the Integrated Sensing and Communications Revolution)** This white paper aims to briefly describe a proposed article that will provide a thorough comparative study of waveforms designed to exploit the features of doubly-dispersive channels arising in heterogeneous high-mobility scenarios as expected in the beyond fifth generation (B5G) and sixth generation (6G), in relation to their suitability to integrated sensing and communications (ISAC) systems. In particular, the full article will compare the well-established delay-Doppler domain-based orthognal time frequency space (OTFS) and the recently proposed chirp domain-based affine frequency division multiplexing (AFDM) waveforms. Both these waveforms are designed based on a full delay- Doppler representation of the time variant (TV) multipath channel, yielding not only robustness and orthogonality of information symbols in high-mobility scenarios, but also a beneficial implication for environment target detection through the inherent capability of estimating the path delay and Doppler shifts, which are standard radar parameters. These modulation schemes are distinct candidates for ISAC in B5G/6G systems, such that a thorough study of their advantages, shortcomings, implications to signal processing, and performance of communication and sensing functions are well in order. In light of the above, a sample of the intended contribution (Special Issue paper) is provided below., Comment: PLEASE FIND THE FULL EXTENDED ARTICLE "From OTFS to AFDM: A Comparative Study of Next-Generation Waveforms for ISAC in Doubly-Dispersive Channels" (Accepted for publication at the IEEE Signal Processing Magazine - Special Issue on Signal Processing for the Integrated Sensing and Communications Revolution)

In the envisioned beyond-fifth-generation (B5G) and sixth-generation (6G) scenarios which expect massive multiple-input multiple-output (mMIMO) and high frequency communications in the millimeter-wave (mmWave) and Terahertz (THz) bands, efficiency in both energy and spectrum is of increasing significance. To that extent, a novel ISAC framework called "sparse codesigned communication and radar (SCCR)" systems is described, which codesigns both communication and radar signals by a sparsification of the resource domain and the waveform spectrum domain. This improves the spectral and energy efficiency, but at the inherent cost of missing radar spectrum and irregular beampattern, and decreased throughput and diversity. Such challenges can however be corroborated, by leveraging various sparsity-robust signal processing techniques such as sparse radar reconstruction and index modulation (IM). In light of the above, the white paper aims to outlined the proposed article which provide an overview and a novel classification of the relevant state-of-the-art (SotA) methods and the implications of the challenges in the sparse codesign of the system, followed by a variety of novel SCCR frameworks.

We consider an uplink integrated sensing and communications (ISAC) scenario where the detection of data symbols from multiple user equipment (UEs) occurs simultaneously with a three-dimensional (3D) estimation of the environment, extracted from the scattering features present in the channel state information (CSI) and utilizing the same physical layer communications air interface, as opposed to radar technologies. By exploiting a discrete (voxelated) representation of the environment, two novel ISAC schemes are derived with purpose-built message passing (MP) rules for the joint estimation of data symbols and status (filled/empty) of the discretized environment. The first relies on a modular feedback structure in which the data symbols and the environment are estimated alternately, whereas the second leverages a bilinear inference framework to estimate both variables concurrently. Both contributed methods are shown via simulations to outperform the state-of-the-art (SotA) in accurately recovering the transmitted data as well as the 3D image of the environment. An analysis of the computational complexities of the proposed methods reveals distinct advantages of each scheme, namely, that the bilinear solution exhibits a superior robustness to short pilots and channel blockages, while the alternating solution offers lower complexity with large number of UEs and superior performance in ideal conditions.

In this paper, we study the maximum number of limit cycles for the piecewise smooth system of differential equations $\dot{x}=y, \ \dot{y}=-x-\varepsilon \cdot (f(x)\cdot y +{\rm sgn}(y)\cdot g(x))$. Using the averaging method, we were able to generalize a previous result for Li\'enard systems. In our generalization, we consider $g$ as a polynomial of degree $m$. We conclude that for sufficiently small values of $|\epsilon|$, the number $\left[\frac{n}{2}\right]+\left[\frac{m}{2}\right]+1$ serves as a lower bound for the maximum number of limit cycles in this system, which bifurcates from the periodic orbits of the linear center $\dot{x}=y$, $\dot{y}=-x$. Furthermore, we demonstrate that it is indeed possible to achieve such a number of limit cycles., Comment: 9 pages, 3 figures

The Drone Swarm Search project is an environment, based on PettingZoo, that is to be used in conjunction with multi-agent (or single-agent) reinforcement learning algorithms. It is an environment in which the agents (drones), have to find the targets (shipwrecked people). The agents do not know the position of the target and do not receive rewards related to their own distance to the target(s). However, the agents receive the probabilities of the target(s) being in a certain cell of the map. The aim of this project is to aid in the study of reinforcement learning algorithms that require dynamic probabilities as inputs., Comment: 6 pages

Atmospheric aerosols influence the Earth's climate, primarily by affecting cloud formation and scattering visible radiation. However, aerosol-related physical processes in climate simulations are highly uncertain. Constraining these processes could help improve model-based climate predictions. We propose a scalable statistical framework for constraining parameters in expensive climate models by comparing model outputs with observations. Using the C3.ai Suite, a cloud computing platform, we use a perturbed parameter ensemble of the UKESM1 climate model to efficiently train a surrogate model. A method for estimating a data-driven model discrepancy term is described. The strict bounds method is applied to quantify parametric uncertainty in a principled way. We demonstrate the scalability of this framework with two weeks' worth of simulated aerosol optical depth data over the South Atlantic and Central African region, written from the model every three hours and matched in time to twice-daily MODIS satellite observations. When constraining the model using real satellite observations, we establish constraints on combinations of two model parameters using much higher time-resolution outputs from the climate model than previous studies. This result suggests that, within the limits imposed by an imperfect climate model, potentially very powerful constraints may be achieved when our framework is scaled to the analysis of more observations and for longer time periods., Comment: 4 figures, 2 tables, submitted to Environmental Data Science

A Round Robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions, and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%, respectively. Due to the added complexity of the structure factor, much fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44% and 86% respectively. This Round Robin experiment highlights several causes for the discrepancies, for which solutions are proposed., Comment: 23 pages, 10 figures. For the original information sent to RR participants, see https://zenodo.org/record/7506365 . For the anonymized results and Jupyter notebook for analysis, see https://zenodo.org/record/7509710

This paper presents our methodology to simulate the behavior of the DeLend Platform. Such simulations are important to verify if the system is able to connect the different sets of agents linked to the platform in a functional manner. They also provide inputs to guide the choices of operational parameters, such as the platform spread, and strategies by DeLend, since they estimate how the key variables of interest respond to different policies. We discuss the methodology and provide examples meant to clarify the approach and to how we intend to use the tool in practice -- they should not be interpreted as representative of real life scenarios.

Glycolaldehyde (HOCH2CHO) is the most straightforward sugar detected in the Interstellar Medium (ISM) and participates in the formation pathways of molecules fundamental to life, red such as ribose and derivatives. Although detected in several regions of the ISM, its formation route is still debated and its abundance cannot be explained only by reactions in the gas phase. This work explores a new gas-phase formation mechanism for glycolaldehyde and compares the energy barrier reduction when the same route happens on the surface of amorphous ices. The first step of the mechanism involves the formation of a carbon-carbon bond between formaldehyde (H2CO) and the formyl radical (HCO), with an energy barrier of 27 kJ mol-1 (gas-phase). The second step consists of barrierless hydrogen addition. Density functional calculations under periodic boundary conditions were applied to study this reaction path on 10 different amorphous ice surfaces through an Eley-Rideal type mechanism. It was found that the energy barrier is reduced on average by 49 per cent, leading in some cases to a 100 per cent reduction. The calculated adsorption energy of glycolaldehyde suggests that it can be promptly desorbed to the gas phase after its formation. This work, thus contributes to explaining the detected relative abundances of glycolaldehyde and opens a new methodological framework for studying the formation routes for Complex Organic Molecules (COMs) in interstellar icy grains., Comment: 10 pages, 9 figures, supplementary data. Accepted for publication in Monthly Notices of the Royal Astronomical Society

We propose a novel, Gaussian signaling mechanism for low probability of detection (LPD) communication systems with either single or multiple antennas. The new scheme is designed to allow the noncoherent detection of Gaussian-distributed signals, enabling LPD communications using signals that follow the complex Gaussian distribution in the time and frequency domains. It is demonstrated via simulations that the proposed scheme achieves better performance than a comparable conventional scheme over the entire SNR region, with the advantage becoming more significant in scenarios with lower overhead., Comment: 5 pages, 3 figures

We investigate strongly correlated many-body systems composed of bosons and fermions with a fully quantum treatment using the path-integral ground state method, PIGS. To account for the Fermi-Dirac statistics, we implement the fixed-node approximation into PIGS, which we then call FN-PIGS. In great detail, we discuss the pair density matrices we use to construct the full density operator in coordinate representation, a vital ingredient of the method. We consider the harmonic oscillator as a proof-of-concept and, as a platform representing quantum many-body systems, we explore helium atoms. Pure $^4$He systems demonstrate most of the features of the method. Complementarily, for pure $^3$He, the fixed-node approximation resolves the ubiquitous sign problem stemming from anti-symmetric wave functions. Finally, we investigate $^3$He-$^4$He mixtures, demonstrating the method's robustness. One of the main features of FN-PIGS is its ability to estimate any property at temperature $T=0$ without any additional bias apart from the FN approximation; biases from long simulations are also excluded. In particular, we calculate the correlation function of pairs of equal and opposite spins and precise values of the $^3$He kinetic energy in the mixture., Comment: 40 pages, 11 figures

The electronic structure of condensed matter can be significantly affected by the electron-phonon interaction, leading to important phenomena such as electrical resistance, superconductivity or the formation of polarons. This interaction is often neglected in band structure calculations but can have a strong impact on band gaps or optical spectra. Commonly used frameworks for electron-phonon energy corrections are the Allen-Heine-Cardona theory and the Fr\"ohlich model. While the latter shows qualitative agreement with experiment for many polar materials, its simplicity should bring hard limits to its applicability in real materials. Improvements can be made by introducing a generalized version of the model, which considers anisotropic and degenerate electronic bands, and multiple phonon branches. In this work, we search for trends and outliers on over a thousand materials in existing databases of phonon and electron band structures. We use our results to identify the limits of applicability of the standard Fr\"olich model by comparing to the generalized version, and by testing its basic hypothesis of a large radius for the polaronic wavefunction and the corresponding atomic displacement cloud. Among our extended set of materials, most exhibit large polaron behavior as well as validity of the perturbative treatment. For the valence band, there is also a significant fraction of the materials for which the perturbative treatment cannot be applied and/or for which the size of the self-trapping region is close to the atomic repetition distance. We find a large variety of behaviors, and employ much more accurate, fully ab initio Allen-Heine-Cardona calculations to understand extreme cases, where the Fr\"ohlich model should fail and unusually large zero-point renormalization energies occur.

In this paper we explore the numerical study. of the Nonlinear Behavior of Suspension Bridge Models. The study of suspension bridges is one of the classic problems of mechanical vibrations, one of the most famous collapses of which was that of the Tacoma Narrows Bridge. This paper covers an initial explanation of vibrations in a suspension bridge. To do this, three different systems are going to be simulated: The first being a system where only the vertical vibrations of the bridge deck are taken into account, the second covering the vibrations of the main cable and the roadbed, and lastly, a system that takes both vertical and torsional vibrations into account. A time-frequency analysis will also be done on all systems with temporal response, Fast Fourier Transform (FFT) and Continuous Wavelet Transform (CWT), plus in a specific case the use of Hilbert-Huang transform (HHT). Poincare maps and Lyapunov exponents are used to characterize the dynamics of the system. In particular, in the vertical and torsional system, an explanation of why the Tacoma Bridge oscillations have undergone an abrupt change from vertical to torsional oscillations. Thus, extremely rich dynamic behaviors are studied by numerical simulation in the time and frequency domains., Comment: 19 pages, 18 Figures

The magnetization of Zn1-xCoxO (0.0055 < x < 0.073) nanoparticles has been measured as a function of temperature T (1.7 K < T , 10 K) and for magnetic field up to 65 kOe using a SQUID magnetometer. Samples were synthesized by three different growth methods: microwave-assisted hydrothermal, combustion reaction and sol-gel. For all studied samples, the magnetic properties derive from the antiferromagnetic (AF) spin clustering due to the Co2+ nearest neighbors. At T >= 6 K, the magnetization of the Co2+ ions has a Brillouin-type behavior, but below 6 K, it shows a notable deviation. We have shown that the observed deviation may be derived from single-ion anisotropy (SIA) with uniaxial symmetry. Results of fits show that the axial-SIA parameter D (typically D = 4.4 K) is slightly larger that the bulk value D = 3.97 K. No significant change of D has been observed as a function of the Co concentration or the growth process. For each sample, the SIA fit gave also the effective concentration (x) corresponding to the technical saturation value of the magnetization. Comparison of the concentration dependence of x with predictions based on cluster models shows an enhancement of the AF spin clustering independent of the growth method. This is ascribed to a clamped non-random distribution of the cobalt ions in the nanoparticles. The approach of the local concentration (xL) has been used to quantify the observed deviation from randomicity. Assuming a ZnO core/ Zn1-xCoxO shell nanoparticle, the thickness of the shell has been determined from the ratio xL/x.

To improve the traveling experience, researchers have been analyzing the role of attitudes in travel behavior modeling. Although most researchers use closed-ended surveys, the appropriate method to measure attitudes is debatable. Topic Modeling could significantly reduce the time to extract information from open-ended responses and eliminate subjective bias, thereby alleviating analyst concerns. Our research uses Topic Modeling to extract information from open-ended questions and compare its performance with closed-ended responses. Furthermore, some respondents might prefer answering questions using their preferred questionnaire type. So, we propose a modeling framework that allows respondents to use their preferred questionnaire type to answer the survey and enable analysts to use the modeling frameworks of their choice to predict behavior. We demonstrate this using a dataset collected from the USA that measures the intention to use Autonomous Vehicles for commute trips. Respondents were presented with alternative questionnaire versions (open- and closed- ended). Since our objective was also to compare the performance of alternative questionnaire versions, the survey was designed to eliminate influences resulting from statements, behavioral framework, and the choice experiment. Results indicate the suitability of using Topic Modeling to extract information from open-ended responses; however, the models estimated using the closed-ended questions perform better compared to them. Besides, the proposed model performs better compared to the models used currently. Furthermore, our proposed framework will allow respondents to choose the questionnaire type to answer, which could be particularly beneficial to them when using voice-based surveys.

Polarons are quasi-particles made from electrons interacting with vibrations in crystal lattices. They derive their name from the strong electron-vibration polar interaction in ionic systems, that induces associated spectroscopic and optical signatures of such quasi-particles in these materials. In this paper, we focus on diamond, a non-polar crystal with inversion symmetry which nevertheless shows characteristic signatures of polarons, better denoted "nonpolarons" in this case. The polaronic effects are produced by short-range crystal fields with only a small influence of long-range quadrupoles. The many-body spectral function has a characteristic energy dependence, showing a plateau structure that is similar to but distinct from the satellites observed in the polar Fr\"{o}hlich case. The temperature-dependent spectral function of diamond is determined by two methods: the standard Dyson-Migdal approach, which calculates electron-phonon interactions within the lowest-order expansion of the self-energy, and the cumulant expansion, which includes higher orders of electron-phonon interactions. The latter corrects the nonpolaron energies and broadening, providing a more realistic spectral function, which we examine in detail for both conduction and valence band edges., Comment: 10 pages 16 Figures + Subfigures 2 Tables 82 References Supplementary Information (SI) at the end: SI 10 pages SI 14 Figures + Subfigures SI 1 Table

We propose a novel physical layer security scheme that exploits an optimization method as a one-way function. The proposed scheme builds on nonsquare differential multiple-input multiple-output (MIMO), which is capable of noncoherent detection even in massive MIMO scenarios and thus resilient against risky pilot insertion and pilot contamination attacks. In contrast to conventional nonsquare differential MIMO schemes, which require space-time projection matrices designed via highly complex, discrete, and combinatorial optimization, the proposed scheme utilizes projection matrices constructed via low-complexity continuous optimization designed to maximize the coding gain of the system. Furthermore, using a secret key generated from the true randomness nature of the wireless channel as an initial value, the proposed continuous optimization-based projection matrix construction method becomes a one-way function, making the proposed scheme a physical layer secure differential MIMO system. An attack algorithm to challenge the proposed scheme is also devised, which demonstrates that the security level achieved improves as the number of transmit antennas increases, even in an environment where the eavesdropper can perfectly estimate channel coefficients and experience asymptotically large signal-to-noise ratios., Comment: 13 pages, 10 figures

The ubiquitous use of sensing and signal processing is increasing exponentially with the advance of the Internet of Everything (IoE). In this context, the design of every time more power efficient sensor nodes is a must. Within these nodes, one of the most power-hungry components are the analog-to-digital converters (ADC). These components are used everywhere to translate real-world analog signals into computer intelligible digital signals. One of the promising architecture for the sensing of physiological signals is the level crossing ADC due to the sparse characteristics of those signals. One of the challenges to improve the power efficiency of this type of ADC lies in the use of continuous comparators to keep track of the input signal within the voltage references. The aim of this work is to investigate the impact of using continuous comparator which can be turned off without incurring error to the conversion of the level crossing ADC. New boundaries will be set for the correct behavior of the level crossing ADC together with the conditions for power saving with the proposed architecture. A 1V 5-bits level crossing ADC was implemented using the TSMC 0.18um process and fabricated for laboratory measurements. The ADC consumes 12.2uW during tracking state and with the proposed technique, the reduction of the average power can go from 4.2% to 45.5% depending on the activity and the type of the input signal.

The level crossing analog-to-digital converters are meant for the effective conversion of sparse signals by construction. In these converters, the bandwidth-power trade-off requires a re-design of the comparators which takes a lot of time and effort to reach the application optimum point. Inspired by synchronous converters that have a dynamic power component that can be traded with bandwidth with the change of a clock frequency, a technique to allow such trade-off in the level crossing converter was developed. The resulting level crossing ADC has an input signal dependent dynamic power which can reach up to 42\% OFF time during the conversion of sine waves, achieving 45.5% power reduction in the simulated design with TSMC 180nm PDK.

The value semigroup $\Gamma$ and the value set $\Lambda$ of $1$-forms are, respectively, a topological and an analytical invariant of a plane branch. Giving a plane branch $\mathcal{C}$ with semigroup $\Gamma$ there are a finitely number of distinct possible sets $\Lambda_i$ according to the analytic class of $\mathcal{C}$. In this work we show that the value set of $1$-forms $\Lambda$ determines the semigroup $\Gamma$ and we present an effective method to recover $\Gamma$ by $\Lambda$. In particular, this allows us to decide if a subset of $\mathbb{N}$ is a value set of $1$-forms for a plane branch.

The value semigroup of a $k$-semiroot $C_k$ of a plane branch $C$ allow us to recover part of the value semigroup $\Gamma =\langle v_0,\ldots ,v_g\rangle$ of $C$, that is, it is related to topological invariants of $C$. In this paper we consider the set of values of differentials $\Lambda_k$ of $C_k$, that is an analytical invariant, and we show how it determine part of the set of values of differentials $\Lambda$ of $C$. As a consequence, in a fixed topological class, we relate the Tjurina number $\tau$ of $C$ with the Tjurina number of $C_k$. In particular, we show that $\tau\leq \mu-\frac{3n_g-2}{4}\mu_{g-1}$ where $n_g=gcd(v_0,\ldots ,v_{g-1})$, $\mu$ and $\mu_{g-1}$ denote the Milnor number of $C$ and $C_{g-1}$ respectively. If $n_g=2$, we have that $\tau=\mu-\mu_{g-1}$ for any curve in the topological class determined by $\Gamma$ that is a generalization of a result obtained by Luengo and Pfister.

Logic synthesis is a fundamental step in hardware design whose goal is to find structural representations of Boolean functions while minimizing delay and area. If the function is completely-specified, the implementation accurately represents the function. If the function is incompletely-specified, the implementation has to be true only on the care set. While most of the algorithms in logic synthesis rely on SAT and Boolean methods to exactly implement the care set, we investigate learning in logic synthesis, attempting to trade exactness for generalization. This work is directly related to machine learning where the care set is the training set and the implementation is expected to generalize on a validation set. We present learning incompletely-specified functions based on the results of a competition conducted at IWLS 2020. The goal of the competition was to implement 100 functions given by a set of care minterms for training, while testing the implementation using a set of validation minterms sampled from the same function. We make this benchmark suite available and offer a detailed comparative analysis of the different approaches to learning, Comment: In this 23 page manuscript, we explore the connection between machine learning and logic synthesis which was the main goal for International Workshop on logic synthesis. It includes approaches applied by ten teams spanning 6 countries across the world

We propose a novel joint activity, channel, and data estimation (JACDE) scheme for cell-free multiple-input multiple-output (MIMO) systems compliant with fifth-generation (5G) new radio (NR) orthogonal frequency-division multiplexing (OFDM) signaling. The contribution aims to allow significant overhead reduction of cell-free MIMO systems by enabling grant-free access, while maintaining moderate throughput per user. To that end, we extend the conventional MIMO OFDM protocol so as to incorporate activity detection capability without resorting to spreading informative data symbols, in contrast with related work which typically relies on signal spreading. Our method leverages a Bayesian message passing scheme based on Gaussian approximation, which jointly performs active user detection (AUD), channel estimation (CE), and multi-user detection (MUD), incorporating also a well-structured low-coherent pilot design based on frame theory, which mitigates pilot contamination, and finally complemented with a detector empowered by bilinear message passing. The efficacy of the resulting JACDE-based grant-free access scheme without spreading data sequences is demonstrated by simulation results, which are shown to significantly outperform the current state-of-the-art and approach the performance of an idealized (genie-aided) scheme in which user activity and channel coefficients are perfectly known., Comment: 15 pages, 15 figures, submitted to an IEEE journal

The search for spontaneous pattern formation in equilibrium phases with genuine quantum properties is a leading direction of current research. In this work we investigate the effect of quantum fluctuations - zero point motion and exchange interactions - on the phases of an ensemble of bosonic particles with isotropic hard-soft corona interactions. We perform extensive path-integral Monte Carlo simulations to determine their ground state properties. A rich phase diagram, parametrized by the density of particles and the interaction strength of the soft-corona potential, reveals supersolid stripes, kagome and triangular crystals in the low-density regime. In the high-density limit we observe patterns with 12-fold rotational symmetry compatible with periodic approximants of quasicrystalline phases. We characterize these quantum phases by computing the superfluid density and the bond-orientational order parameter. Finally, we highlight the qualitative and quantitative differences of our findings with the classical equilibrium phases for the same parameter regimes., Comment: 5+4 pages, 9 figures

We consider a bidirectional in-band full-duplex (FD) multiple-input multiple-output (MIMO) system subject to imperfect channel state information (CSI), hardware distortion, and limited analog cancellation capability as well as the self-interference (SI) power requirement at the receiver analog domain so as to avoid the saturation of low noise amplifier (LNA). A novel minimum mean square error (MMSE)-based joint design of digital precoder and combiner for SI cancellation is offered, which combines the well-known gradient projection method and non-monotonicity considered in recent machine-learning literature in order to tackle the non-convexity of the optimization problem formulated in this article. Simulation results illustrate the effectiveness of the proposed SI cancellation algorithm., Comment: 7 pages, 2 figures, submitted to an IEEE conference

We present a novel algorithm for the completion of low-rank matrices whose entries are limited to a finite discrete alphabet. The proposed method is based on the recently-emerged proximal gradient (PG) framework of optimization theory, which is applied here to solve a regularized formulation of the completion problem that includes a term enforcing the discrete-alphabet membership of the matrix entries., Comment: 5 pages, 2 figures, submitted to an IEEE conference

We present a framework for the design of low-complexity and high-performance receivers for multidimensional overloaded NOMA systems. The framework is built upon a novel compressive sensing (CS) regularized maximum likelihood formulation of the discrete-input detection problem, in which the L0-norm is introduced to enforce adherence of the solution to the prescribed discrete symbol constellation. Unlike much of preceding literature, the method is not relaxed into the L1-norm, but rather approximated with a continuous and asymptotically exact expression without resorting to parallel interference cancellation. The objective function of the resulting formulation is thus a sum of concave-over-convex ratios, which is then tightly convexized via the quadratic transform, such that its solution can be obtained via the iteration of a simple closed-form expression that closely resembles that of the classic zero-forcing (ZF) receiver. By further transforming the aforementioned problem into a quadratically constrained quadratic program with one convex constraint (QCQP-1), the optimal regularization parameter to be used at each step of the iterative algorithm is then shown to be the largest generalized eigenvalue of a pair of matrices which are given in closed-form. The method so obtained, referred to as the IDLS, is then extended to address several factors of practical relevance, such as noisy conditions, imperfect CSI, and hardware impairments, thus yielding the Robust IDLS algorithm. Simulation results show that the proposed art significantly outperforms both classic receivers, such as the LMMSE, and recent CS-based alternatives, such as the SOAV and the SCSR detectors., Comment: Submitted to the IEEE for possible publication