72 citations · 134 across the 8 of their papers we have counts for
8 papers
DFT-p-FDMA Based Chirp Transmission in CP-OFDM for Unified ISAC Waveform Design
Fabrizio Carpi, Joonyoung Cho, Kyeong Jin Kim +1
We propose an integrated sensing and communications (ISAC) framework that supports chirp signal transmission in CP-OFDM-based multiple access communication systems, enabling effici…
Learning-Based Compress-and-Forward Schemes for the Relay Channel
Ezgi Ozyilkan, Fabrizio Carpi, Siddharth Garg +1
The relay channel, consisting of a source-destination pair along with a relay, is a fundamental component of cooperative communications. While the capacity of a general relay chann…
Learned Pulse Shaping Design for PAPR Reduction in DFT-s-OFDM
Fabrizio Carpi, Soheil Rostami, Joonyoung Cho +3
High peak-to-average power ratio (PAPR) is one of the main factors limiting cell coverage for cellular systems, especially in the uplink direction. Discrete Fourier transform sprea…
Neural Compress-and-Forward for the Relay Channel
Ezgi Ozyilkan, Fabrizio Carpi, Siddharth Garg +1
The relay channel, consisting of a source-destination pair and a relay, is a fundamental component of cooperative communications. While the capacity of a general relay channel rema…
Precoding-oriented Massive MIMO CSI Feedback Design
Fabrizio Carpi, Sivarama Venkatesan, Jinfeng Du +3
Downlink massive multiple-input multiple-output (MIMO) precoding algorithms in frequency division duplexing (FDD) systems rely on accurate channel state information (CSI) feedback…
Single-Shot Compression for Hypothesis Testing
Fabrizio Carpi, Siddharth Garg, Elza Erkip
Enhanced processing power in the cloud allows constrained devices to offload costly computations: for instance, complex data analytics tasks can be computed by remote servers. Remo…
Reinforcement Learning for Channel Coding: Learned Bit-Flipping Decoding
Fabrizio Carpi, Christian Häger, Marco Martalò +2
In this paper, we use reinforcement learning to find effective decoding strategies for binary linear codes. We start by reviewing several iterative decoding algorithms that involve…
Learned Belief-Propagation Decoding with Simple Scaling and SNR Adaptation
Mengke Lian, Fabrizio Carpi, Christian Häger +1
We consider the weighted belief-propagation (WBP) decoder recently proposed by Nachmani et al. where different weights are introduced for each Tanner graph edge and optimized using…