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Giuseppe Caire

7 accepted papers

2024

Semantic-Preserving Image Coding Based on Conditional Diffusion Models

ICASSP 2024accepted

Semantic communication, rather than on a bit-by-bit recovery of the transmitted messages, focuses on the meaning and the goal of the communication itself. In this paper, we propose a novel semantic image coding scheme that preserves the semantic content of an image, while ensuring a good trade-off b…

Cited by 0SourceScholar
2023

Neurally Augmented State Space Model for Simultaneous Communication and Tracking with Low Complexity Receivers

ICASSP 2023accepted

In this paper, we propose an integrated sensing and communications (ISAC) system where a base station (BS) equipped with an antenna array and a co-located radar receiver transmits data packets while simultaneously tracking the position of users. We restrict our attention to the simplest hardware arc…

Cited by 0SourceScholar
2023

The First Pathloss Radio Map Prediction Challenge

ICASSP 2023accepted

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. In this short overview paper, we briefly describe the pathloss prediction problem, the provided datasets,…

Cited by 0SourceScholar
2022

LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning

ICASSP 2022accepted

This paper deals with the problem of localization in a cellular network in a dense urban scenario. Global Navigation Satellite Systems (GNSS) typically perform poorly in urban environments, where the likelihood of line-of-sight conditions is low, and thus alternative localization methods are require…

Cited by 0SourceScholar
2022

On the Potential of Spatially-Spread Orthogonal Time Frequency Space Modulation for ISAC Transmissions

ICASSP 2022accepted

In this paper, we study the potentials of spatially-spread orthogonal time frequency space (SS-OTFS) modulation for integrated sensing and communication (ISAC) transmissions. The most favourable feature of SS-OTFS modulation is that it forms beams according to a pre-determined angular grid, which is…

Cited by 0SourceScholar
2020

Pathloss Prediction using Deep Learning with Applications to Cellular Optimization and Efficient D2D Link Scheduling

ICASSP 2020accepted

In this paper we propose a highly efficient and very accurate method for estimating the propagation pathloss from a point x to all points y on the 2D plane. Our method, termed RadioUNet, is a deep neural network. For applications such as user-cell site association and device-to-device (D2D) link sch…

Cited by 26SourceScholar