Search Results for author:
Found 31 papers, 11 papers with code
Distributed U6G ELAA Communication Systems: Channel Measurement and Small-Scale Fading Characterization
The distributed upper 6 GHz (U6G) extra-large scale antenna array (ELAA) is a key enabler for future wireless communication systems, offering higher throughput and wider coverage, similar to existing ELAA systems, while effectively mitigating unaffordable complexity and hardware overhead.
Deep-Unfolded Massive Grant-Free Transmission in Cell-Free Wireless Communication Systems
This paper proposes a novel framework of joint active user detection, channel estimation, and data detection (JACD) for massive grant-free transmission in cell-free wireless communication systems.
CovNet: Covariance Information-Assisted CSI Feedback for FDD Massive MIMO Systems
In this paper, we propose a novel covariance information-assisted channel state information (CSI) feedback scheme for frequency-division duplex (FDD) massive multi-input multi-output (MIMO) systems.
A Tensor-Structured Approach to Dynamic Channel Prediction for Massive MIMO Systems with Temporal Non-Stationarity
Furthermore, we model cross-domain correlations of ADD domain channels within each frame, induced by clustered scattering, through the Markov random field and tensor-coupled Gaussian distribution that incorporates high-order neighboring structures.
Low-Coherence Sequence Design Under PAPR Constraints
Low-coherence sequences with low peak-to-average power ratio (PAPR) are crucial for multi-carrier wireless communication systems and are used for pilots, spreading sequences, and so on.
Ubiquitous Integrated Sensing and Communications for Massive MIMO LEO Satellite Systems
The next sixth generation (6G) networks are envisioned to integrate sensing and communications in a single system, thus greatly improving spectrum utilization and reducing hardware costs.
$\text{Memory}^3$: Language Modeling with Explicit Memory
The model is named $\text{Memory}^3$, since explicit memory is the third form of memory in LLMs after implicit memory (model parameters) and working memory (context key-values).
Polar-Coded Tensor-Based Unsourced Random Access with Soft Decoding
The unsourced random access (URA) has emerged as a viable scheme for supporting the massive machine-type communications (mMTC) in the sixth generation (6G) wireless networks.
Towards Unified AI Models for MU-MIMO Communications: A Tensor Equivariance Framework
In this paper, we propose a unified framework based on equivariance for the design of artificial intelligence (AI)-assisted technologies in multi-user multiple-input-multiple-output (MU-MIMO) systems.
Joint Channel Estimation and Prediction for Massive MIMO with Frequency Hopping Sounding
This paper aims to investigate joint channel estimation and prediction (JCEP) for massive MIMO with frequency hopping sounding (FHS).
Robust Symbol-Level Precoding for Massive MIMO Communication Under Channel Aging
With the signal model in the presence of channel aging, we formulate the signal-to-noise-plus-interference ratio (SINR) balancing and minimum mean square error (MMSE) problems for robust SLP design.
CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models
For each of these CRUD categories, we have developed comprehensive datasets to evaluate the performance of RAG systems.
Privacy Protected Contactless Cardio-respiratory Monitoring using Defocused Cameras during Sleep
The monitoring of vital signs such as heart rate (HR) and respiratory rate (RR) during sleep is important for the assessment of sleep quality and detection of sleep disorders.
Grimoire is All You Need for Enhancing Large Language Models
In this paper, we propose a method SLEICL that involves learning from examples using strong language models and then summarizing and transferring these learned skills to weak language models for inference and application.
Beam-Delay Domain Channel Estimation for mmWave XL-MIMO Systems
This paper investigates the uplink channel estimation of the millimeter-wave (mmWave) extremely large-scale multiple-input-multiple-output (XL-MIMO) communication system in the beam-delay domain, taking into account the near-field and beam-squint effects due to the transmission bandwidth and array aperture growth.
Soft Demodulator for Symbol-Level Precoding in Coded Multiuser MISO Systems
It is observed that the received SLP signals do not always follow Gaussian distribution, rendering the conventional soft demodulation with the Gaussian assumption unsuitable for the coded SLP systems.
Symbol-Level Precoding for Average SER Minimization in Multiuser MISO Systems
This paper investigates symbol-level precoding (SLP) for high-order quadrature amplitude modulation (QAM) aimed at minimizing the average symbol error rate (SER), leveraging both constructive interference (CI) and noise power to gain superiority in full signal-to-noise ratio (SNR) ranges.
Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering
Instead, in this paper, we find that instruction-tuning language models like Claude and ChatGPT can understand layout by spaces and line breaks.
Ranked #9 on
Visual Question Answering (VQA)
on DocVQA test
Task Difficulty Aware Parameter Allocation & Regularization for Lifelong Learning
In this paper, we propose the Parameter Allocation & Regularization (PAR), which adaptively select an appropriate strategy for each task from parameter allocation and regularization based on its learning difficulty.
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding
Recent years have witnessed the rise and success of pre-training techniques in visually-rich document understanding.
Ranked #2 on
Semantic entity labeling
on FUNSD
ERNIE-mmLayout: Multi-grained MultiModal Transformer for Document Understanding
At first, a document graph is proposed to model complex relationships among multi-grained multimodal elements, in which salient visual regions are detected by a cluster-based method.
Estimating Human Weight from A Single Image
In this case, the widely used Body Mass Index (BMI) which is associated with body height and weight can be employed as a measure of weight to indicate the health conditions.
LiteGEM: Lite Geometry Enhanced Molecular Representation Learning for Quantum Property Prediction
In this report, we (SuperHelix team) present our solution to KDD Cup 2021-PCQM4M-LSC, a large-scale quantum chemistry dataset on predicting HOMO-LUMO gap of molecules.
Algorithmic Principles of Camera-based Respiratory Motion Extraction
Measuring the respiratory signal from a video based on body motion has been proposed and recently matured in products for video health monitoring.
Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification
Graph neural network (GNN) and label propagation algorithm (LPA) are both message passing algorithms, which have achieved superior performance in semi-supervised classification.
Ranked #1 on
Node Property Prediction
on ogbn-proteins
Network Massive MIMO Transmission Over Millimeter-Wave and Terahertz Bands: Mobility Enhancement and Blockage Mitigation
Based on these insights, the network massive MIMO precoding design is reduced to a network sum-rate maximization problem with respect to beam domain power allocation.
Spectral Efficiency and Energy Efficiency Tradeoff in Massive MIMO Downlink Transmission with Statistical CSIT
As a key technology for future wireless networks, massive multiple-input multiple-output (MIMO) can significantly improve the energy efficiency (EE) and spectral efficiency (SE), and the performance is highly dependant on the degree of the available channel state information (CSI).
Lifelong Learning with Searchable Extension Units
To solve those problems, in this paper, we propose a new lifelong learning framework named Searchable Extension Units (SEU) by introducing Neural Architecture Search into lifelong learning, which breaks down the need for a predefined original model and searches for specific extension units for different tasks, without compromising the performance of the model on different tasks.
2.75D: Boosting learning by representing 3D Medical imaging to 2D features for small data
Such performance gain is more pronounced with transfer learning or in the case of limited training data.
Analysis of CNN-based remote-PPG to understand limitations and sensitivities
Finally, we conclude that the PPG-related prior knowledge is still helpful for the CNN-based PPG extraction.
Learning to Localize: A 3D CNN Approach to User Positioning in Massive MIMO-OFDM Systems
In this paper, we consider the user positioning problem in the massive multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system with a uniform planner antenna (UPA) array.
