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Found 42 papers, 5 papers with code
Sensing in Bi-Static ISAC Systems with Clock Asynchronism: A Signal Processing Perspective
Integrated Sensing and Communications (ISAC) has been identified as a pillar usage scenario for the impending 6G era.
Radio Map Estimation -- An Open Dataset with Directive Transmitter Antennas and Initial Experiments
Over the last years, several works have explored the application of deep learning algorithms to determine the large-scale signal fading (also referred to as ``path loss'') between transmitter and receiver pairs in urban communication networks.
A New Old Idea: Beam-Steering Reflectarrays for Efficient Sub-THz Multiuser MIMO
We present a novel, power- & hardware-efficient, multiuser, multibeam RIS (Reflective Intelligent Surface) architecture for multiuser MIMO, especially for very high frequency bands (e. g., high mmWave and sub-THz), where channels are typically sparse in the beamspace and LOS is the dominant component.
From OTFS to DD-ISAC: Integrating Sensing and Communications in the Delay Doppler Domain
The recently proposed Orthogonal Time Frequency Space (OTFS) modulation, which exploits various advantages of Delay Doppler (DD) channels, has been shown to support reliable communication in high-mobility scenarios.
The First Pathloss Radio Map Prediction Challenge
To foster research and facilitate fair comparisons among recently proposed pathloss radio map prediction methods, we have launched the ICASSP 2023 First Pathloss Radio Map Prediction Challenge.
Multi-static Parameter Estimation in the Near/Far Field Beam Space for Integrated Sensing and Communication Applications
The proposed parameter estimation in this work consists of a two-stage estimation process, where the first stage is based on far-field assumptions, and is used to obtain a first estimate of the target parameters.
Extended Target Parameter Estimation and Tracking with an HDA Setup for ISAC Applications
We investigate radar parameter estimation and beam tracking with a hybrid digital-analog (HDA) architecture in a multi-block measurement framework using an extended target model.
Power Transfer between Two Antenna Arrays in the Near Field
Furthermore, the behavior of the power transmission coefficient is more sensitive to the $F/D$ ratio than to a particular RIS size.
Beam Alignment with an Intelligent Reflecting Surface for Integrated Sensing and Communication
In a typical communication system, in order to maintain a desired SNR level, initial beam alignment (BA) must be established prior to data transmission.
ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment
In this paper, we propose ByzSecAgg, an efficient secure aggregation scheme for federated learning that is protected against Byzantine attacks and privacy leakages.
Non-uniform array design for robust LoS MIMO via convex optimization
To that end, the joint design of nonuniform Tx and Rx arrays towards maximizing the minimum capacity of a LoS MIMO system across a range of transmit distances is investigated in this paper.
On the Effective Usage of Priors in RSS-based Localization
In this paper, we study the localization problem in dense urban settings.
Dataset of Pathloss and ToA Radio Maps With Localization Application
In this article, we present a collection of radio map datasets in dense urban setting, which we generated and made publicly available.
Rate Loss due to Beam Cusping in Grid of Beams
We consider array antenna elements with non-zero aperture and axisymmetric radiation pattern with a certain directivity, unlike the ideal isotropic antenna elements widely considered in theoretical papers on array processing and RF beamforming.
RIS-Based Steerable Beamforming Antenna with Near-Field Eigenmode Feeder
For a given AMAF aperture, the optimal AMAF-RIS distance increases as a function of the RIS size.
A Beam-Space Active Sensing Scheme for Integrated Communication and Sensing Applications
In this paper, we develop an active sensing strategy for a millimeter wave (mmWave) band Integrated Sensing and Communication (ISAC) system adopting a realistic hybrid digital-analog (HDA) architecture.
Beam-Space MIMO Radar for Joint Communication and Sensing with OTFS Modulation
Under this setup, we propose a likelihood function-based scheme to perform joint target detection and parameter estimation in Discovery, and high-resolution parameter estimation in Tracking mode, respectively.
Simultaneous Communication and Tracking in Arbitrary Trajectories via Beam-Space Processing
In this paper, we develop a beam tracking scheme for an orthogonal frequency division multiplexing (OFDM) Integrated Sensing and Communication (ISAC) system with a hybrid digital analog (HDA) architecture operating in the millimeter wave (mmWave) band.
SwiftAgg+: Achieving Asymptotically Optimal Communication Loads in Secure Aggregation for Federated Learning
We propose SwiftAgg+, a novel secure aggregation protocol for federated learning systems, where a central server aggregates local models of $N \in \mathbb{N}$ distributed users, each of size $L \in \mathbb{N}$, trained on their local data, in a privacy-preserving manner.
SwiftAgg: Communication-Efficient and Dropout-Resistant Secure Aggregation for Federated Learning with Worst-Case Security Guarantees
We propose SwiftAgg, a novel secure aggregation protocol for federated learning systems, where a central server aggregates local models of $N$ distributed users, each of size $L$, trained on their local data, in a privacy-preserving manner.
LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning
We present LocUNet: A deep learning method for localization, based merely on Received Signal Strength (RSS) from Base Stations (BSs), which does not require any increase in computation complexity at the user devices with respect to the device standard operations, unlike methods that rely on time of arrival or angle of arrival information.
Integrated Sensing and Communications for V2I Networks: Dynamic Predictive Beamforming for Extended Vehicle Targets
The first stage is exploited for ISAC transmission, where a wide beam is adopted for both communication and sensing.
DNN-assisted Particle-based Bayesian Joint Synchronization and Localization
In particular, DePF deploys an asymmetric time-stamp exchange mechanism between the MUs and the Access Points (APs), which, traditionally, provides us with information about the MUs' clock offset and skew.
Real-time Outdoor Localization Using Radio Maps: A Deep Learning Approach
Global Navigation Satellite Systems typically perform poorly in urban environments, where the likelihood of line-of-sight conditions between devices and satellites is low.
A New Design of Cache-aided Multiuser Private Information Retrieval with Uncoded Prefetching
This paper considers the MuPIR problem with two messages, arbitrary number of users and databases where uncoded prefetching is assumed, i. e., the users directly copy some bits from the library as their cached contents.
On Secure Distributed Linearly Separable Computation
Then we focus on the case where the computation cost of each server is minimum and aim to minimize the size of the randomness variable introduced in the system while achieving the optimal communication cost.
Information Theory Information Theory
Low Latency Scheduling Algorithms for Full-Duplex V2X Networks
Vehicular communication systems have been an active subject of research for many years and are important technologies in the 5G and the post-5G era.
Autonomous Driving
Information Theory
Signal Processing
Information Theory
Cache-aided General Linear Function Retrieval
Coded Caching, proposed by Maddah-Ali and Niesen (MAN), has the potential to reduce network traffic by pre-storing content in the users' local memories when the network is underutilized and transmitting coded multicast messages that simultaneously benefit many users at once during peak-hour times.
Information Theory Information Theory
A Novel Transformation Approach of Shared-link Coded Caching Schemes for Multiaccess Networks
Applying the transformation approach to the well-known shared-link coded caching scheme proposed by Maddah-Ali and Niesen, we obtain a new multiaccess coded caching scheme that achieves the same load as the scheme of Hachem et al. but for any system parameters.
Information Theory Information Theory
Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution Imaging
More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters.
Classification of Spot-welded Joints in Laser Thermography Data using Convolutional Neural Networks
Spot welding is a crucial process step in various industries.
On the Fundamental Limits of Cache-aided Multiuser Private Information Retrieval
Based on the proposed novel approach of \emph{cache-aided interference alignment (CIA)}, first, for the MuPIR problem with $K=2$ messages, $K_{\rm u}=2$ users and $N\ge 2$ databases, we propose achievable retrieval schemes for both uncoded and general cache placement.
Hybrid Digital-Analog Beamforming and MIMO Radar with OTFS Modulation
The second scenario considers narrow angular beams to send information streams individually to the already detected users and simultaneously keep tracking of their respective parameters.
Real-time Localization Using Radio Maps
Using the approximations of the pathloss functions of all base stations and the reported signal strengths, we are able to extract a very accurate approximation of the location of the user.
RadioUNet: Fast Radio Map Estimation with Convolutional Neural Networks
In this paper we propose a highly efficient and very accurate deep learning method for estimating the propagation pathloss from a point $x$ (transmitter location) to any point $y$ on a planar domain.
Machine Learning for Geometrically-Consistent Angular Spread Function Estimation in Massive MIMO
The modern literature on massive MIMO has recognized that the knowledge of covariance matrix of user channel vectors is very useful for various applications such as hybrid digital analog beamforming, pilot decontamination, etc.
Multiple Measurement Vectors Problem: A Decoupling Property and its Applications
Although there is a vast literature on the analysis of MMV, it is not yet fully known how the number of signal samples and their statistical correlations affects the performance of the joint estimation in MMV.
Multi-Band Covariance Interpolation with Applications in Massive MIMO
In this paper, we show that although this effect is generally negligible for a small number of antennas $M$, it results in a considerable distortion of the covariance matrix and especially its dominant signal subspace in the massive MIMO regime where $M \to \infty$, and can generally incur a serious degradation of the performance especially in frequency division duplexing (FDD) massive MIMO systems where the uplink (UL) and the downlink (DL) communication occur over different frequency bands.
Compressive Estimation of a Stochastic Process with Unknown Autocorrelation Function
To design such a blind predictor, we use the random spectral representation of a stationary Gaussian process.
Signal Recovery from Unlabeled Samples
In this paper, we study the recovery of a signal from a set of noisy linear projections (measurements), when such projections are unlabeled, that is, the correspondence between the measurements and the set of projection vectors (i. e., the rows of the measurement matrix) is not known a priori.
Channel Vector Subspace Estimation from Low-Dimensional Projections
Massive MIMO is a variant of multiuser MIMO where the number of base-station antennas $M$ is very large (typically 100), and generally much larger than the number of spatially multiplexed data streams (typically 10).
