Zobrazeno 1 - 10
of 1 002
pro vyhledávání: '"Yuan, XIaojun"'
Compressive Robust Principal Component Analysis (CRPCA) naturally arises in various applications as a means to recover a low-rank matrix low-rank matrix $\boldsymbol{L}$ and a sparse matrix $\boldsymbol{S}$ from compressive measurements. In this pape
Externí odkaz:
http://arxiv.org/abs/2412.03106
This work considers an uplink asynchronous massive random access scenario in which a large number of users asynchronously access a base station equipped with multiple receive antennas. The objective is to alleviate the problem of massive collision du
Externí odkaz:
http://arxiv.org/abs/2411.01923
This paper introduces Bifr\"ost, a novel 3D-aware framework that is built upon diffusion models to perform instruction-based image composition. Previous methods concentrate on image compositing at the 2D level, which fall short in handling complex sp
Externí odkaz:
http://arxiv.org/abs/2410.19079
Autor:
Yang, Huiyuan, Yuan, Xiaojun
This paper studies the second-order achievabilities of indirect quadratic lossy source coding for a specific class of source models, where the term "quadratic" denotes that the reconstruction fidelity of the hidden source is quantified by a squared e
Externí odkaz:
http://arxiv.org/abs/2410.08110
Existing diffusion-based methods for inverse problems sample from the posterior using score functions and accept the generated random samples as solutions. In applications that posterior mean is preferred, we have to generate multiple samples from th
Externí odkaz:
http://arxiv.org/abs/2410.05646
Channel knowledge map (CKM) is viewed as a digital twin of wireless channels, providing location-specific channel knowledge for environment-aware communications. A fundamental problem in CKM-assisted communications is how to construct the CKM efficie
Externí odkaz:
http://arxiv.org/abs/2409.00461
This paper addresses the problem of end-to-end (E2E) design of learning and communication in a task-oriented semantic communication system. In particular, we consider a multi-device cooperative edge inference system over a wireless multiple-input mul
Externí odkaz:
http://arxiv.org/abs/2408.17397
In this paper, we propose a learning-based block-wise planar channel estimator (LBPCE) with high accuracy and low complexity to estimate the time-varying frequency-selective channel of a multiple-input multiple-output (MIMO) orthogonal frequency-divi
Externí odkaz:
http://arxiv.org/abs/2405.11218
This paper studies a passive localization system, where an extremely large-scale antenna array (ELAA) is deployed at the base station (BS) to locate a user equipment (UE) residing in its near-field (Fresnel) region. We propose a novel algorithm, name
Externí odkaz:
http://arxiv.org/abs/2406.17784
To exploit unprecedented data generation in mobile edge networks, federated learning (FL) has emerged as a promising alternative to the conventional centralized machine learning (ML). However, there are some critical challenges for FL deployment. One
Externí odkaz:
http://arxiv.org/abs/2403.06653