Search Results for author: Zhen Gao

Found 26 papers, 4 papers with code

Deep Joint Semantic Coding and Beamforming for Near-Space Airship-Borne Massive MIMO Network

no code implementations30 May 2024 Minghui Wu, Zhen Gao, Zhaocheng Wang, Dusit Niyato, George K. Karagiannidis, Sheng Chen

Specifically, we propose a deep joint semantic coding and beamforming (JSCBF) scheme for airship-based massive MIMO image transmission network in space, in which semantics from both source and channel are fused to jointly design the semantic coding and physical layer beamforming.

Image Reconstruction Semantic Communication

Three-layer deep learning network random trees for fault diagnosis in chemical production process

no code implementations1 May 2024 Ming Lu, Zhen Gao, Ying Zou, Zuguo Chen, Pei Li

With the development of technology, the chemical production process is becoming increasingly complex and large-scale, making fault diagnosis particularly important.

Dependability Evaluation of Stable Diffusion with Soft Errors on the Model Parameters

no code implementations30 Mar 2024 Zhen Gao, Lini Yuan, Pedro Reviriego, Shanshan Liu, Fabrizio Lombardi

In this paper, the dependability of Stable Diffusion is studied focusing on soft errors in the memory that stores the model parameters; specifically, errors are injected into some critical layers of the Transformer in different blocks of the image information creator, to evaluate their impact on model performance.

Image Generation

Concurrent Linguistic Error Detection (CLED) for Large Language Models

no code implementations25 Mar 2024 Jinhua Zhu, Javier Conde, Zhen Gao, Pedro Reviriego, Shanshan Liu, Fabrizio Lombardi

Since the proposed error detection mechanism only relies on the outputs of the model, then it can be used on LLMs in which there is no access to the internal nodes.

News Summarization valid

Distributed Multi-Objective Dynamic Offloading Scheduling for Air-Ground Cooperative MEC

no code implementations16 Mar 2024 Yang Huang, Miaomiao Dong, Yijie Mao, Wenqiang Liu, Zhen Gao

Due to such design and the kernel-based neural network, to which decision-making features can be continuously added, the kernel-based approach can outperform the approach based on fully-connected deep neural network, yielding improvement in energy consumption and the backlog performance, as well as a significant reduction in decision-making and online learning time.

Decision Making Edge-computing +3

Block-Sparse Tensor Recovery

no code implementations4 Feb 2024 Liyang Lu, Zhaocheng Wang, Zhen Gao, Sheng Chen, H. Vincent Poor

This work explores the fundamental problem of the recoverability of a sparse tensor being reconstructed from its compressed embodiment.

Transformer-based Joint Source Channel Coding for Textual Semantic Communication

no code implementations23 Jul 2023 Shicong Liu, Zhen Gao, Gaojie Chen, Yu Su, Lu Peng

The Space-Air-Ground-Sea integrated network calls for more robust and secure transmission techniques against jamming.

Semantic Communication Semantic Similarity +2

Hybrid Knowledge-Data Driven Channel Semantic Acquisition and Beamforming for Cell-Free Massive MIMO

no code implementations6 Jul 2023 Zhen Gao, Shicong Liu, Yu Su, Zhongxiang Li, Dezhi Zheng

Moreover, based on the acquired channel semantic, we further propose a knowledge-driven deep-unfolding multi-user beamformer, which is capable of achieving good spectral efficiency with robustness to imperfect CSI in outdoor XR scenarios.

Concurrent Classifier Error Detection (CCED) in Large Scale Machine Learning Systems

no code implementations2 Jun 2023 Pedro Reviriego, Ziheng Wang, Alvaro Alonso, Zhen Gao, Farzad Niknia, Shanshan Liu, Fabrizio Lombardi

In this paper, we introduce Concurrent Classifier Error Detection (CCED), a scheme to implement CED in ML systems using a concurrent ML classifier to detect errors.

Image Classification

Sensing User's Channel and Location with Terahertz Extra-Large Reconfigurable Intelligent Surface under Hybrid-Field Beam Squint Effect

no code implementations12 May 2023 Zhuoran Li, Zhen Gao, Tuan Li

Specifically, we first propose a joint channel and location sensing scheme, which consists of a location-assisted generalized multiple measurement vector orthogonal matching pursuit (LA-GMMV-OMP) algorithm for channel estimation (CE) and a complete dictionary based localization (CDL) scheme, where a frequency selective polar-domain redundant dictionary is proposed to overcome the hybrid field beam squint effect.


Multiple-Antenna Aided Aeronautical Communications in Air-Ground Integrated Networks: Channel Estimation, Reliable Transmission, and Multiple Access

no code implementations15 Jan 2023 Jingjing Zhao, YanBo Zhu, Kaiquan Cai, Zhen Gao, Zhu Han, Lajos Hanzo

To provide seamless coverage during all flight phases, aeronautical communications systems (ACS) have to integrate space-based, air-based, as well as ground-based platforms to formulate aviation-oriented space-air-ground integrated networks (SAGINs).


Grant-Free NOMA-OTFS Paradigm: Enabling Efficient Ubiquitous Access for LEO Satellite Internet-of-Things

no code implementations25 Sep 2022 Zhen Gao, Xingyu Zhou, Jingjing Zhao, Juan Li, Chunli Zhu, Chun Hu, Pei Xiao, Symeon Chatzinotas, Derrick Wing Kwan Ng, Bjorn Ottersten

With the blooming of Internet-of-Things (IoT), we are witnessing an explosion in the number of IoT terminals, triggering an unprecedented demand for ubiquitous wireless access globally.

Deep Learning-Based Rate-Splitting Multiple Access for Reconfigurable Intelligent Surface-Aided Tera-Hertz Massive MIMO

no code implementations18 Sep 2022 Minghui Wu, Zhen Gao, Yang Huang, Zhenyu Xiao, Derrick Wing Kwan Ng, Zhaoyang Zhang

Then, to acquire accurate CSI at the BS for the investigated RSMA precoding scheme to achieve higher spectral efficiency, we propose a CSI acquisition network (CAN) with low pilot and feedback signaling overhead, where the downlink pilot transmission, CSI feedback at the user equipments (UEs), and CSI reconstruction at the BS are modeled as an end-to-end neural network based on Transformer.

Transformer-Empowered 6G Intelligent Networks: From Massive MIMO Processing to Semantic Communication

no code implementations8 May 2022 Yang Wang, Zhen Gao, Dezhi Zheng, Sheng Chen, Deniz Gündüz, H. Vincent Poor

It is anticipated that 6G wireless networks will accelerate the convergence of the physical and cyber worlds and enable a paradigm-shift in the way we deploy and exploit communication networks.

Semantic Communication

Fault-Tolerant Deep Learning: A Hierarchical Perspective

no code implementations5 Apr 2022 Cheng Liu, Zhen Gao, Siting Liu, Xuefei Ning, Huawei Li, Xiaowei Li

With the rapid advancements of deep learning in the past decade, it can be foreseen that deep learning will be continuously deployed in more and more safety-critical applications such as autonomous driving and robotics.

Autonomous Driving

Data-Driven Deep Learning Based Hybrid Beamforming for Aerial Massive MIMO-OFDM Systems with Implicit CSI

no code implementations18 Jan 2022 Zhen Gao, Minghui Wu, Chun Hu, Feifei Gao, Guanghui Wen, Dezhi Zheng, Jun Zhang

To this end, by modeling the key transmission modules as an end-to-end (E2E) neural network, this paper proposes a data-driven deep learning (DL)-based unified hybrid beamforming framework for both the time division duplex (TDD) and frequency division duplex (FDD) systems with implicit channel state information (CSI).

Quantization Transfer Learning

LEO Satellite Constellations for 5G and Beyond: How Will They Reshape Vertical Domains?

no code implementations18 Jun 2021 Shicong Liu, Zhen Gao, Yongpeng Wu, Derrick Wing Kwan Ng, Xiqi Gao, Kai-Kit Wong, Symeon Chatzinotas, Bjorn Ottersten

The rapid development of communication technologies in the past decades has provided immense vertical opportunities for individuals and enterprises.

Model-Driven Deep Learning Based Channel Estimation and Feedback for Millimeter-Wave Massive Hybrid MIMO Systems

no code implementations22 Apr 2021 Xisuo Ma, Zhen Gao, Feifei Gao, Marco Di Renzo

To reduce the uplink pilot overhead for estimating the high-dimensional channels from a limited number of radio frequency (RF) chains at the base station (BS), we propose to jointly train the phase shift network and the channel estimator as an auto-encoder.

Terahertz Ultra-Massive MIMO-Based Aeronautical Communications in Space-Air-Ground Integrated Networks

no code implementations2 Mar 2021 Anwen Liao, Zhen Gao, Dongming Wang, Hua Wang, Hao Yin, Derrick Wing Kwan Ng, Mohamed-Slim Alouini

According to the proposed prior-aided iterative angle estimation algorithm, azimuth/elevation angles can be estimated, and these angles are adopted to achieve precise beam-alignment and refine GTTDU module for further eliminating delay-beam squint.

Information Theory Signal Processing Information Theory

Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces

2 code implementations3 Jun 2020 Shicong Liu, Zhen Gao, Jun Zhang, Marco Di Renzo, Mohamed-Slim Alouini

Integrating large intelligent reflecting surfaces (IRS) into millimeter-wave (mmWave) massive multi-input-multi-ouput (MIMO) has been a promising approach for improved coverage and throughput.

Compressive Sensing Denoising

FTT-NAS: Discovering Fault-Tolerant Convolutional Neural Architecture

1 code implementation20 Mar 2020 Xuefei Ning, Guangjun Ge, Wenshuo Li, Zhenhua Zhu, Yin Zheng, Xiaoming Chen, Zhen Gao, Yu Wang, Huazhong Yang

By inspecting the discovered architectures, we find that the operation primitives, the weight quantization range, the capacity of the model, and the connection pattern have influences on the fault resilience capability of NN models.

Neural Architecture Search Quantization

Data-Driven Deep Learning to Design Pilot and Channel Estimator For Massive MIMO

no code implementations12 Mar 2020 Xisuo Ma, Zhen Gao

Specifically, we design an end-to-end deep neural network (DNN) architecture composed of dimensionality reduction network and reconstruction network to respectively mimic the pilot signals and channel estimator, which can be acquired by data-driven deep learning.

Compressive Sensing Dimensionality Reduction

A Novel Multiple Classifier Generation and Combination Framework Based on Fuzzy Clustering and Individualized Ensemble Construction

1 code implementation31 Jul 2019 Zhen Gao, Maryam Zand, Jianhua Ruan

In testing, ICE finds the k most similar training instances for a testing instance, then predicts class label of the testing instance by averaging the prediction from models associated with these training instances.

Clustering General Classification

Compressive Sensing Based Adaptive Active User Detection and Channel Estimation: Massive Access Meets Massive MIMO

no code implementations24 Jun 2019 Malong Ke, Zhen Gao, Yongpeng Wu, Xiqi Gao, Robert Schober

This paper considers massive access in massive multiple-input multiple-output (MIMO) systems and proposes an adaptive active user detection and channel estimation scheme based on compressive sensing.

Compressive Sensing

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