pwc-archive/papers-with-abstracts huggingface dataset:
Adaptive Detection of Dim Maneuvering Targets in Adjacent Range Cells
Authors: Sheng Yan, Pia Addabbo, Chengpeng Hao, Danilo Orlando
Date: 2021-03-07 00:00:00

This letter addresses the detection problem of dim maneuvering targets in the presence of range cell migration. Specifically, it is assumed that the moving target can appear in more than one range cell within the transmitted pulse train. Then, the Bayesian information criterion and the generalized likelihood ratio test design procedure are jointly exploited to come up with six adaptive decision schemes capable of estimating the range indices related to the target migration. The computational complexity of the proposed detectors is also studied and suitably reduced. Simulation results show the effectiveness of the newly proposed solutions also for a limited set of training data and in comparison with suitable counterparts.
SCMA Codebook Design Based on Uniquely Decomposable Constellation Groups
Authors: Xuewan Zhang, Dalong Zhang, Liuqing Yang, Gangtao Han, Hsiao-Hwa Chen, Di Zhang
Date: 2021-02-27 00:00:00

Sparse code multiple access (SCMA), which helps improve spectrum efficiency (SE) and enhance connectivity, has been proposed as a non-orthogonal multiple access (NOMA) scheme for 5G systems. In SCMA, codebook design determines system overload ratio and detection performance at a receiver. In this paper, an SCMA codebook design approach is proposed based on uniquely decomposable constellation group (UDCG). We show that there are $N+1 (N \geq 1)$ constellations in the proposed UDCG, each of which has $M (M \geq 2)$ constellation points. These constellations are allocated to users sharing the same resource. Combining the constellations allocated on multiple resources of each user, we can obtain UDCG-based codebook sets. Bit error ratio (BER) performance will be discussed in terms of coding gain maximization with superimposed constellations and UDCG-based codebooks. Simulation results demonstrate that the superimposed constellation of each resource has large minimum Euclidean distance (MED) and meets uniquely decodable constraint. Thus, BER performance of the proposed codebook design approach outperforms that of the existing codebook design schemes in both uncoded and coded SCMA systems, especially for large-size codebooks.
Analysis and Optimization for RIS-Aided Multi-Pair Communications Relying on Statistical CSI
Authors: Zhangjie Peng, Tianshu Li, Cunhua Pan, Hong Ren, Wei Xu, Marco Di Renzo
Date: 2020-07-22 00:00:00
Tasks: Quantization

In this paper, we investigate a reconfigurable intelligent surface (RIS) aided multi-pair communication system, in which multi-pair users exchange information via an RIS. We derive an approximate expression of the achievable rate by assuming that statistical channel state information (CSI) is available. A genetic algorithm (GA) to solve the rate maximization problem is proposed as well. In particular, we consider implementations of RISs with continuous phase shifts (CPSs) and discrete phase shifts (DPSs). Simulation results verify the correctness of the obtained results and show that the proposed GA method has almost the same performance as the globally optimal solution. In addition, numerical results show that three quantization bits can achieve a large portion of the sum achievable rate for the CPSs setup.
Hybrid Relay-Reflecting Intelligent Surface-Assisted Wireless Communication
Authors: Nhan Thanh Nguyen, Quang-Doanh Vu, Kyungchun Lee, Markku Juntti
Date: 2021-03-05 00:00:00

Reconfigurable intelligent surface (RIS) has emerged as a cost- and energy-efficient solution to enhance the wireless communication capacity. However, recent studies show that a very large surface is required for a RIS-assisted communication system; otherwise, they may be outperformed by the conventional relay. Furthermore, the performance gain of a RIS can be considerably degraded by hardware impairments such as limited-resolution phase shifters. To overcome those challenges, we propose a novel concept of hybrid relay-reflecting intelligent surface (HR-RIS), in which a single or few elements are deployed with power amplifiers (PAs) to serve as active relays, while the remaining elements only reflect the incident signals. Two architectures are proposed, including the fixed and dynamic HR-RIS. Their coefficient matrices are obtained based on alternating optimization (AO) and power allocation strategies, which enable understanding the fundamental performances of RIS and relaying-based systems with a trade-off between the two. The simulation results show that a significant improvement in both the spectral efficiency (SE) and energy efficiency (EE) with respect to the conventional RIS-aided system can be attained by the proposed schemes, especially, by the dynamic HR-RIS. In particular, the favorable design and deployment of the HR-RIS are analytically derived and numerically justified.
OFDM with Index Modulation in Orbital Angular Momentum Multiplexed Free Space Optical Links
Authors: El-Mehdi Amhoud, Marwa Chafii, Ahmad Nimr, Gerhard Fettweis
Date: 2021-03-05 00:00:00

Communication using orbital angular momentum (OAM) modes has recently received a considerable interest in free space optical (FSO) communications. Propagating OAM modes through free space may be subject to atmospheric turbulence (AT) distortions that cause signal attenuation and crosstalk which degrades the system capacity and increases the error probability. In this paper, we propose to enhance the OAM FSO communications in terms of bit error rate and spectral efficiency, for different levels of AT regimes. The performance gain is achieved by introducing orthogonal frequency division multiplexing (OFDM) with index modulation technique to the OAM FSO system.
Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction
Authors: Chaithya G R, Zaccharie Ramzi, Philippe Ciuciu
Date: 2021-03-05 00:00:00
Tasks: compressed sensing, Image Reconstruction

The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. It yields non-Cartesian sampling trajectories that jointly fulfill a target sampling density while each individual trajectory complies with MR hardware constraints. However, the two main limitations of SPARKLING are first that the optimal target sampling density is unknown and thus a user-defined parameter and second that this sampling pattern generation remains disconnected from MR image reconstruction thus from the optimization of image quality. Recently, datadriven learning schemes such as LOUPE have been proposed to learn a discrete sampling pattern, by jointly optimizing the whole pipeline from data acquisition to image reconstruction. In this work, we merge these methods with a state-of-the-art deep neural network for image reconstruction, called XPDNET, to learn the optimal target sampling density. Next, this density is used as input parameter to SPARKLING to obtain 20x accelerated non-Cartesian trajectories. These trajectories are tested on retrospective compressed sensing (CS) studies and show superior performance in terms of image quality with both deep learning (DL) and conventional CS reconstruction schemes.
A Comprehensive Investigation on Range-free Localization Algorithms with Mobile Anchors at Different Altitudes
Authors: Francesco Betti Sorbelli, Sajal K. Das, Cristina M. Pinotti, Giulio Rigoni
Date: 2021-02-10 00:00:00

In this work, the problem of localizing ground devices (GDs) is studied comparing the performance of four range-free (RF) localization algorithms that use a mobile anchor (MA). All the investigated algorithms are based on the so-called heard/not-heard (HnH) method, which allows the GDs to detect the MA at the border of their antenna communication radius. Despite the simplicity of this method, its efficacy in terms of accuracy is poor because it relies on the antenna radius that continuously varies under different conditions. Usually, the antenna radius declared by the manufacturer does not fully characterize the actual antenna radiation pattern. In this paper, the radiation pattern of the commercial DecaWave DWM1001 Ultra-Wide-Band (UWB) antennas is observed in a real test-bed at different altitudes for collecting more information and insights on the antenna radius. The compared algorithms are then tested using both the observed and the manufacturer radii. The experimental accuracy is close to the expected theoretical one only when the antenna pattern is actually omnidirectional. However, typical antennas have strong pattern irregularities that decrease the accuracy. For improving the performance, we propose range-based (RB) variants of the compared algorithms in which, instead of using the observed or the manufacturer radii, the actual measured distances between the MA and the GD are used. The localization accuracy tremendously improves confirming that the knowledge of the exact antenna pattern is essential for any RF algorithm.
Testing for a Random Walk Structure in the Frequency Evolution of a Tone in Noise
Authors: S. E. Abramson, W. Moran, R. J. Evans, A. Melatos
Date: 2021-03-05 00:00:00
Tasks: Time Series, Time Series Analysis

Inference and hypothesis testing are typically constructed on the basis that a specific model holds for the data. To determine the veracity of conclusions drawn from such data analyses, one must be able to identify the presence of the assumed structure within the data. In this paper, a model verification test is developed for the presence of a random walk-like structure in the variations in the frequency of complex-valued sinusoidal signals measured in additive Gaussian noise. This test evaluates the joint inference of the random walk hypothesis tests found in economics literature that seek random walk behaviours in time series data, with an additional test to account for how the random walk behaves in frequency space.
Super-resolution Method for Coherent DOA Estimation of Multiple Wideband Sources
Authors: Milad Javadzadeh Jirhandeh, Mohammad Hossein Kahaei
Date: 2021-03-04 00:00:00
Tasks: Direction of Arrival Estimation, Super-Resolution

We focus on coherent direction of arrival estimation of wideband sources based on spatial sparsity. This area of research is encountered in many applications such as passive radar, sonar, mining, and communication problems, in which an increasing attention has been devoted to improving the estimation accuracy and robustness to noise. By the development of super-resolution algorithms, narrowband direction of arrival estimation based on gridless sparse algorithms and atomic norm minimization has already been addressed. In this paper, a superresolution based method is proposed for coherent direction of arrival estimation of multiple wideband sources. First, unlike the conventional coherent methods, we develop a new focusing method to map the subband with the largest center frequency to the other ones, which leads to an accurate method with no requirement for initial estimates for DOAs. Then, we introduce an atomic norm problem by defining a new set of atoms and exploiting the signal joint sparsity of different frequency subbands in a continuous spatial domain. This problem is then cast as a semidefinite program, which leads to implementing a new coherent direction of arrival estimation method with higher resolution and more robustness to noise. Our method needs only one single snapshot for each frequency subband, leading to a small number of snapshots for the received wideband signal compared to the other coherent DOA techniques. Numerical simulations show the outperformance of the proposed method compared to the conventional ones.
Hybrid Interference Mitigation Using Analog Prewhitening
Authors: Wei zhang, Yi Jiang, Bin Zhou, Die Hu
Date: 2021-03-04 00:00:00

This paper proposes a novel scheme for mitigating strong interferences, which is applicable to various wireless scenarios, including full-duplex wireless communications and uncoordinated heterogenous networks. As strong interferences can saturate the receiver's analog-to-digital converters (ADC), they need to be mitigated both before and after the ADCs, i.e., via hybrid processing. The key idea of the proposed scheme, namely the Hybrid Interference Mitigation using Analog Prewhitening (HIMAP), is to insert an M-input M-output analog phase shifter network (PSN) between the receive antennas and the ADCs to spatially prewhiten the interferences, which requires no signal information but only an estimate of the covariance matrix. After interference mitigation by the PSN prewhitener, the preamble can be synchronized, the signal channel response can be estimated, and thus a minimum mean squared error (MMSE) beamformer can be applied in the digital domain to further mitigate the residual interferences. The simulation results verify that the HIMAP scheme can suppress interferences 80dB stronger than the signal by using off-the-shelf phase shifters (PS) of 6-bit resolution.
Sub-Terahertz and mmWave Penetration Loss Measurements for Indoor Environments
Authors: Kairui Du, Ozgur Ozdemir, Fatih Erden, Ismail Guvenc
Date: 2021-03-03 00:00:00

Millimeter-wave (mmWave) and terahertz (THz) spectrum can support significantly higher data rates compared to lower frequency bands and hence are being actively considered for 5G wireless networks and beyond. These bands have high free-space path loss (FSPL) in line-of-sight (LOS) propagation due to their shorter wavelength. Moreover, in non-line-of-sight (NLOS) scenario, these two bands suffer higher penetration loss than lower frequency bands which could seriously affect the network coverage. It is therefore critical to study the NLOS penetration loss introduced by different building materials at mmWave and THz bands, to help establish link budgets for an accurate performance analysis in indoor environments. In this work, we measured the penetration loss and the attenuation of several common constructional materials at mmWave (28 and 39 GHz) and sub-THz (120 and 144 GHz) bands. Measurements were conducted using a channel sounder based on NI PXI platforms. Results show that the penetration loss changes extensively based on the frequency and the material properties, ranging from 0.401 dB for ceiling tile at 28 GHz, to 16.608 dB for plywood at 144 GHz. Ceiling tile has the lowest measured attenuation at 28 GHz, while clear glass has the highest attenuation of 27.633 dB/cm at 144 GHz. As expected, the penetration loss and attenuation increased with frequency for all the tested materials.
Adaptive Transmission for Distributed Detection in Energy Harvesting Wireless Sensor Networks
Authors: Ghazaleh Ardeshiri, Azadeh Vosoughi
Date: 2021-03-03 00:00:00
Tasks: Quantization

We consider a wireless sensor network, consisting of N heterogeneous sensors and a fusion center (FC), tasked with detecting a known signal in uncorrelated Gaussian noises. Each sensor can harvest randomly arriving energy and store it in a finite-size battery. Sensors communicate directly with the FC over orthogonal fading channels. Each sensor adapts its transmit symbol power, such that the larger its stored energy and its quantized channel gain are, the higher its transmit symbol power is. To strike a balance between energy harvesting and energy consumption, we formulate two constrained optimization problems (P1) and (P2), where in both problems we seek the jointly optimal local decision thresholds and channel gain quantization thresholds. While in (P1) we maximize the Jdivergence of the received signal densities at the FC, in (P2) we minimize the average total transmit power, subject to certain constraints. We solve (P1) and (P2), assuming that the batteries reach their steady-state. Our simulation results demonstrate the effectiveness of our optimization on enhancing the detection performance in (P1), and lowering the average total transmit power in (P2). They also reveal how the energy harvesting rate, the battery size, the sensor observation and communication channel parameters impact obtained solutions.
Stability of Neural Networks on Riemannian Manifolds
Authors: Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Date: 2021-03-03 00:00:00

Convolutional Neural Networks (CNNs) have been applied to data with underlying non-Euclidean structures and have achieved impressive successes. This brings the stability analysis of CNNs on non-Euclidean domains into notice because CNNs have been proved stable on Euclidean domains. This paper focuses on the stability of CNNs on Riemannian manifolds. By taking the Laplace-Beltrami operators into consideration, we construct an $\alpha$-frequency difference threshold filter to help separate the spectrum of the operator with an infinite dimensionality. We further construct a manifold neural network architecture with these filters. We prove that both the manifold filters and neural networks are stable under absolute perturbations to the operators. The results also implicate a trade-off between the stability and discriminability of manifold neural networks. Finally we verify our conclusions with numerical experiments in a wireless adhoc network scenario.
Semidefinite Programming Two-way TOA Localization for User Devices with Motion and Clock Drift
Authors: Sihao Zhao, Xiao-Ping Zhang, Xiaowei Cui, Mingquan Lu
Date: 2021-03-03 00:00:00

In two-way time-of-arrival (TOA) systems, a user device (UD) obtains its position by round-trip communications to a number of anchor nodes (ANs) at known locations. The objective function of the maximum likelihood (ML) method for two-way TOA localization is nonconvex. Thus, the widely-adopted Gauss-Newton iterative method to solve the ML estimator usually suffers from the local minima problem. In this paper, we convert the original estimator into a convex problem by relaxation, and develop a new semidefinite programming (SDP) based localization method for moving UDs, namely SDP-M. Numerical result demonstrates that compared with the iterative method, which often fall into local minima, the SDP-M always converge to the global optimal solution and significantly reduces the localization error by more than 40%. It also has stable localization accuracy regardless of the UD movement, and outperforms the conventional method for stationary UDs, which has larger error with growing UD velocity.
Rate Analysis and Deep Neural Network Detectors for SEFDM FTN Systems
Authors: Arsenia Chorti, David Picard
Date: 2021-03-03 00:00:00

In this work we compare the capacity and achievable rate of uncoded faster than Nyquist (FTN) signalling in the frequency domain, also referred to as spectrally efficient FDM (SEFDM). We propose a deep residual convolutional neural network detector for SEFDM signals in additive white Gaussian noise channels, that allows to approach the Mazo limit in systems with up to 60 subcarriers. Notably, the deep detectors achieve a loss less than 0.4-0.7 dB for uncoded QPSK SEFDM systems of 12 to 60 subcarriers at a 15% spectral compression.
The generalized method of moments for multi-reference alignment
Authors: Asaf Abas, Tamir Bendory, Nir Sharon
Date: 2021-03-03 00:00:00

This paper studies the application of the generalized method of moments (GMM) to multi-reference alignment (MRA): the problem of estimating a signal from its circularly-translated and noisy copies. We begin by proving that the GMM estimator maintains its asymptotic optimality for statistical models with group symmetry, including MRA. Then, we conduct a comprehensive numerical study and show that the GMM substantially outperforms the classical method of moments, whose application to MRA has been studied thoroughly in the literature. We also formulate the GMM to estimate a three-dimensional molecular structure using cryo-electron microscopy and present numerical results on simulated data.
Real Time Vigilance Detection using Frontal EEG
Authors: Siddarth Ganesh, Ram Gurumoorthy
Date: 2021-03-03 00:00:00
Tasks: Brain Computer Interface, EEG, Electroencephalogram (EEG)

Vigilance of an operator is compromised in performing many monotonous activities like workshop and manufacturing floor tasks, driving, night shift workers, flying, and in general any activity which requires keen attention of an individual over prolonged periods of time. Driver or operator fatigue in these situations leads to drowsiness and lowered vigilance which is one of the largest contributors to injuries and fatalities amongst road accidents or workshop floor accidents. Having a vigilance monitoring system to detect drop in vigilance in these situations becomes very important. This paper presents a system which uses non-invasively recorded Frontal EEG from an easy-to-use commercially available Brain Computer Interface wearable device to determine the vigilance state of an individual. The change in the power spectrum in the Frontal Theta Band (4-8Hz) of an individual's brain wave predicts the changes in the attention level of an individual - providing an early detection and warning system. This method provides an accurate, yet cheap and practical system for vigilance monitoring across different environments.
SCUBA: An In-Device Multiplexed Protocol for Sidelink Communication on Unlicensed Bands
Authors: Vishnu Rajendran, Gautham Prasad, Lutz Lampe, Gus Vos
Date: 2020-12-07 00:00:00

Device-to-device communication (D2D) is a key enabler for connecting devices together to form the Internet of Things (IoT). A growing issue with IoT networks is the increasing number of IoT devices congesting the spectral resources of the cellular bands. Operating D2D in unlicensed band alleviates this issue by offloading network traffic from the licensed bands, while also reducing the associated licensing costs. To this end, we present a new low-cost radio access technology (RAT) protocol, called Sidelink Communications on Unlicensed BAnds (SCUBA), which can be implemented on cellular devices such that it coexists with the legacy cellular protocol by operating as a secondary RAT in a time division duplex manner using the existing radio hardware. SCUBA is compatible on different types of cellular devices including the low-complexity half-duplex frequency division duplex machine type communication (MTC) user equipments. SCUBA provides flexible sidelink (SL) latency and battery life tradeoff using a discontinuous reception procedure, which ensures that it is applicable across a wide range of use cases. We prove the effectiveness of our protocol with analyses and simulation results of the medium access control layer of SCUBA using different types of MTC traffic for both SL and the underlying cellular communication.
Scheduling Optimization of Heterogeneous Services by Resolving Conflicts
Authors: Sotiris Skaperas, Nasim Ferdosian, Arsenia Chorti, Lefteris Mamatas
Date: 2021-03-02 00:00:00
Tasks: Scheduling

Fifth generation (5G) new radio introduced flexible numerology to provide the necessary flexibility for accommodating heterogeneous services. However, optimizing the scheduling of heterogeneous services with differing delay and throughput requirements over 5G new radio is a challenging task. In this paper, we investigate near optimal, low complexity scheduling of radio resources for ultra-reliable low-latency communications (URLLC) when coexisting with enhanced mobile broadband (eMBB) services. We demonstrate that maximizing the sum throughput of eMBB services while servicing URLLC users, is, in the long-term, equivalent to minimizing the number of URLLC placements in the time-frequency grid; this result stems from reducing the number of infeasible placements for eMBB, to which we refer to as "conflicts". To meet this new objective, we propose and investigate new conflict-aware heuristics; a family of "greedy" and a lightweight heuristic inspired by bin packing optimization, all of near optimal performance. Moreover, having shed light on the impact of conflict in layer-2 scheduling, non-orthogonal multiple access (NOMA) emerges as a competitive approach for conflict resolution, in addition to the well established increased spectral efficiency with respect to OMA. The superior performance of NOMA, thanks to alleviating conflicts,is showcased by extensive numerical results.