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Found 17 papers, 4 papers with code
Performance Bounds for Passive Sensing in Asynchronous ISAC Systems -- Appendices
This document contains the appendices for our paper titled ``Performance Bounds for Passive Sensing in Asynchronous ISAC Systems."
Reshaping the ISAC Tradeoff Under OFDM Signaling: A Probabilistic Constellation Shaping Approach
To cope with this issue, we characterize the random AF of OFDM communication signals, and demonstrate that the AF variance is determined by the fourth-moment of the constellation amplitudes.
Communication-Assisted Sensing in 6G Networks
Exploring the mutual benefit and reciprocity of sensing and communication (S\&C) functions is fundamental to realizing deeper integration for integrated sensing and communication (ISAC) systems.
Probabilistic Constellation Shaping for OFDM-Based ISAC Signaling
Integrated Sensing and Communications (ISAC) has garnered significant attention as a promising technology for the upcoming sixth-generation wireless communication systems (6G).
Light Field Diffusion for Single-View Novel View Synthesis
Starting from the camera pose matrices, LFD transforms them into light field encoding, with the same shape as the reference image, to describe the direction of each ray.
Sensing With Random Signals
Radar systems typically employ well-designed deterministic signals for target sensing.
Waveform Design for Communication-Assisted Sensing in 6G Perceptive Networks
In particular, a pair of transmission schemes, namely, separated S&C and dual-functional waveform designs, are proposed to optimize the sensing QoS under the constraints of the rate-distortion and power budget.
MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask Generation
Then, we use an image sequence generator and semantic diffusion refiner conditioned on the generated mask sequences to produce realistic 3D medical images that align with the generated masks.
Rethinking Estimation Rate for Wireless Sensing: A Rate-Distortion Perspective
Wireless sensing has been recognized as a key enabling technology for numerous emerging applications.
Semantic Adversarial Attacks on Face Recognition through Significant Attributes
The probability score method is based on training a Face Verification model for an attribute prediction task to obtain a class probability score for each attribute.
Joint Receiver Design for Integrated Sensing and Communications
In this letter, we investigate the joint receiver design for integrated sensing and communication (ISAC) systems, where the communication signal and the target echo signal are simultaneously received and processed to achieve a balanced performance between both functionalities.
On the Performance Gain of Integrated Sensing and Communications: A Subspace Correlation Perspective
In this paper, we shed light on the performance gain of integrated sensing and communications (ISAC) from the perspective of channel correlations between radar sensing and communication (S&C), namely ISAC subspace correlation.
Sampling-based Fast Gradient Rescaling Method for Highly Transferable Adversarial Attacks
Deviation between the original gradient and the generated noises may lead to inaccurate gradient update estimation and suboptimal solutions for adversarial transferability, which is crucial for black-box attacks.
Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability
The black-box adversarial attack has attracted impressive attention for its practical use in the field of deep learning security.
Stochastic Variance Reduced Ensemble Adversarial Attack
Black-box adversarial attack has attracted much attention for its practical use in deep learning applications, and it is very challenging as there is no access to the architecture and weights of the target model.
Detecting Textual Adversarial Examples through Randomized Substitution and Vote
Based on this observation, we propose a novel textual adversarial example detection method, termed Randomized Substitution and Vote (RS&V), which votes the prediction label by accumulating the logits of k samples generated by randomly substituting the words in the input text with synonyms.
Sampling Overhead Analysis of Quantum Error Mitigation: Uncoded vs. Coded Systems
Quantum error mitigation (QEM) is a promising technique of protecting hybrid quantum-classical computation from decoherence, but it suffers from sampling overhead which erodes the computational speed.
Quantum Physics Information Theory Information Theory
