Search Results for author: Giuseppe Caire

Found 25 papers, 4 papers with code

Simultaneous Communication and Tracking in Arbitrary Trajectories via Beam-Space Processing

no code implementations29 Mar 2022 Fernando Pedraza, Saeid K. Dehkordi, Mari Kobayashi, Giuseppe Caire

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

no code implementations24 Mar 2022 Tayyebeh Jahani-Nezhad, Mohammad Ali Maddah-Ali, Songze Li, Giuseppe Caire

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.

Federated Learning

SwiftAgg: Communication-Efficient and Dropout-Resistant Secure Aggregation for Federated Learning with Worst-Case Security Guarantees

no code implementations8 Feb 2022 Tayyebeh Jahani-Nezhad, Mohammad Ali Maddah-Ali, Songze Li, Giuseppe Caire

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.

Federated Learning

LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning

1 code implementation1 Feb 2022 Çağkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire

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.

DNN-assisted Particle-based Bayesian Joint Synchronization and Localization

no code implementations29 Sep 2021 Meysam Goodarzi, Vladica Sark, Nebojsa Maletic, Jesús Gutiérrez, Giuseppe Caire, Eckhard Grass

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

1 code implementation23 Jun 2021 Çağkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire

In the proposed method, the user to be localized simply reports such received signal strengths to a central processing unit, which may be located in the cloud.

A New Design of Cache-aided Multiuser Private Information Retrieval with Uncoded Prefetching

no code implementations2 Feb 2021 Xiang Zhang, Kai Wan, Hua Sun, Mingyue Ji, Giuseppe Caire

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.

Information Retrieval

On Secure Distributed Linearly Separable Computation

no code implementations1 Feb 2021 Kai Wan, Hua Sun, Mingyue Ji, Giuseppe Caire

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

no code implementations13 Jan 2021 Michail Palaiologos, Jian Luo, Richard A. Stirling-Gallacher, Giuseppe Caire

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

no code implementations28 Dec 2020 Kai Wan, Hua Sun, Mingyue Ji, Daniela Tuninetti, Giuseppe Caire

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

no code implementations8 Dec 2020 Minquan Cheng, Dequan Liang, Kai Wan, Mingming Zhang, Giuseppe Caire

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

2 code implementations7 Dec 2020 Samim Ahmadi, Jan Christian Hauffen, Linh Kästner, Peter Jung, Giuseppe Caire, Mathias Ziegler

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.

Super-Resolution

On the Fundamental Limits of Cache-aided Multiuser Private Information Retrieval

no code implementations13 Oct 2020 Xiang Zhang, Kai Wan, Hua Sun, Mingyue Ji, Giuseppe Caire

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.

Information Retrieval

Hybrid Digital-Analog Beamforming and MIMO Radar with OTFS Modulation

no code implementations17 Sep 2020 Lorenzo Gaudio, Mari Kobayashi, Giuseppe Caire, Giulio Colavolpe

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

no code implementations9 Jun 2020 Çağkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire

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

1 code implementation17 Nov 2019 Ron Levie, Çağkan Yapar, Gitta Kutyniok, Giuseppe Caire

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

no code implementations30 Oct 2019 Yi Song, Mahdi Barzegar Khalilsarai, Saeid Haghighatshoar, Giuseppe Caire

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

no code implementations31 Oct 2018 Saeid Haghighatshoar, Giuseppe Caire

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

no code implementations11 Jan 2018 Saeid Haghighatshoar, Mahdi Barzegar Khalilsarai, Giuseppe Caire

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.

Signal Recovery from Unlabeled Samples

no code implementations30 Jan 2017 Saeid Haghighatshoar, Giuseppe Caire

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

no code implementations24 Sep 2015 Saeid Haghighatshoar, Giuseppe Caire

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).

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