Search Results for author: Branka Vucetic

Found 30 papers, 1 papers with code

Semantic-aware Transmission Scheduling: a Monotonicity-driven Deep Reinforcement Learning Approach

no code implementations23 May 2023 Jiazheng Chen, Wanchun Liu, Daniel Quevedo, Yonghui Li, Branka Vucetic

For cyber-physical systems in the 6G era, semantic communications connecting distributed devices for dynamic control and remote state estimation are required to guarantee application-level performance, not merely focus on communication-centric performance.

Decision Making reinforcement-learning +1

Untrained Neural Network based Bayesian Detector for OTFS Modulation Systems

no code implementations8 May 2023 Hao Chang, Alva Kosasih, Wibowo Hardjawana, Xinwei Qu, Branka Vucetic

In this paper, we propose an untrained DNN based on the deep image prior (DIP) and decoder architecture, referred to as D-DIP that replaces the MMSE denoiser in the iterative detector.

A Novel Exploitative and Explorative GWO-SVM Algorithm for Smart Emotion Recognition

no code implementations5 Jan 2023 Xucun Yan, Zihuai Lin, Zhiyun Lin, Branka Vucetic

Therefore, our aim is to find a reliable and efficient emotion recognition scheme, which can be used for non-behavior-based emotion recognition in real-time.

Emotion Recognition

Structure-Enhanced DRL for Optimal Transmission Scheduling

no code implementations24 Dec 2022 Jiazheng Chen, Wanchun Liu, Daniel E. Quevedo, Saeed R. Khosravirad, Yonghui Li, Branka Vucetic

In addition, we show that the derived structural properties exist in a wide range of dynamic scheduling problems that go beyond remote state estimation.


A Scalable Graph Neural Network Decoder for Short Block Codes

no code implementations13 Nov 2022 Kou Tian, Chentao Yue, Changyang She, Yonghui Li, Branka Vucetic

In this work, we propose a novel decoding algorithm for short block codes based on an edge-weighted graph neural network (EW-GNN).

Signal Detection in MIMO Systems with Hardware Imperfections: Message Passing on Neural Networks

no code implementations8 Oct 2022 Dawei Gao, Qinghua Guo, Guisheng Liao, Yonina C. Eldar, Yonghui Li, Yanguang Yu, Branka Vucetic

Modelling the MIMO system with NN enables the design of NN architectures based on the signal flow of the MIMO system, minimizing the number of NN layers and parameters, which is crucial to achieving efficient training with limited pilot signals.

Bayesian Inference

Deep Learning for Wireless Networked Systems: a joint Estimation-Control-Scheduling Approach

no code implementations3 Oct 2022 Zihuai Zhao, Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic

Wireless networked control system (WNCS) connecting sensors, controllers, and actuators via wireless communications is a key enabling technology for highly scalable and low-cost deployment of control systems in the Industry 4. 0 era.


Interference-Limited Ultra-Reliable and Low-Latency Communications: Graph Neural Networks or Stochastic Geometry?

no code implementations11 Jul 2022 Yuhong Liu, Changyang She, Yi Zhong, Wibowo Hardjawana, Fu-Chun Zheng, Branka Vucetic

In this paper, we aim to improve the Quality-of-Service (QoS) of Ultra-Reliability and Low-Latency Communications (URLLC) in interference-limited wireless networks.

Bayesian Neural Network Detector for an Orthogonal Time Frequency Space Modulation

no code implementations27 Jun 2022 Alva Kosasih, Xinwei Qu, Wibowo Hardjawana, Chentao Yue, Branka Vucetic

The orthogonal time-frequency space (OTFS) modulation is proposed for beyond 5G wireless systems to deal with high mobility communications.

Bayesian Inference

Graph Neural Network Aided MU-MIMO Detectors

1 code implementation19 Jun 2022 Alva Kosasih, Vincent Onasis, Vera Miloslavskaya, Wibowo Hardjawana, Victor Andrean, Branka Vucetic

Multi-user multiple-input multiple-output (MU-MIMO) systems can be used to meet high throughput requirements of 5G and beyond networks.

DRL-based Resource Allocation in Remote State Estimation

no code implementations24 May 2022 Gaoyang Pang, Wanchun Liu, Yonghui Li, Branka Vucetic

Existing algorithms on dynamic radio resource allocation for remote estimation systems assumed oversimplified wireless communications models and can only work for small-scale settings.

Decision Making

Stability Conditions for Remote State Estimation of Multiple Systems over Semi-Markov Fading Channels

no code implementations31 Mar 2022 Wanchun Liu, Daniel E. Quevedo, Branka Vucetic, Yonghui Li

In particular, we show that, from a system stability perspective, fast fading channels may be preferable to slow fading ones.

Significant Low-dimensional Spectral-temporal Features for Seizure Detection

no code implementations13 Feb 2022 Xucun Yan, Dongping Yang, Zihuai Lin, Branka Vucetic

Seizure onset detection in electroencephalography (EEG) signals is a challenging task due to the non-stereotyped seizure activities as well as their stochastic and non-stationary characteristics in nature.

Electroencephalogram (EEG) Seizure Detection

Bayesian-based Symbol Detector for Orthogonal Time Frequency Space Modulation Systems

no code implementations27 Oct 2021 Xinwei Qu, Alva Kosasih, Wibowo Hardjawana, Vincent Onasis, Branka Vucetic

Our simulation results show that in contrast to the state-of-the-art OTFS detectors, the proposed detector is able to achieve a BER of less than $10^{-5}$, when SNR is over $14$ dB, under high ICI environments.

Improving Cell-Free Massive MIMO Detection Performance via Expectation Propagation

no code implementations27 Oct 2021 Alva Kosasih, Vera Miloslavskaya, Wibowo Hardjawana, Victor Andrean, Branka Vucetic

The simulation results show that the proposed detector achieves significant improvements in terms of the bit-error rate and sum spectral efficiency performances as compared to the ones of the state-of-the-art CF detectors.

Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control

no code implementations26 Sep 2021 Wanchun Liu, Kang Huang, Daniel E. Quevedo, Branka Vucetic, Yonghui Li

We consider a joint uplink and downlink scheduling problem of a fully distributed wireless networked control system (WNCS) with a limited number of frequency channels.

reinforcement-learning Reinforcement Learning (RL) +1

Stability Conditions for Remote State Estimation of Multiple Systems over Multiple Markov Fading Channels

no code implementations9 Apr 2021 Wanchun Liu, Daniel E. Quevedo, Karl H. Johansson, Branka Vucetic, Yonghui Li

We investigate the stability conditions for remote state estimation of multiple linear time-invariant (LTI) systems over multiple wireless time-varying communication channels.


Knowledge-Assisted Deep Reinforcement Learning in 5G Scheduler Design: From Theoretical Framework to Implementation

no code implementations17 Sep 2020 Zhouyou Gu, Changyang She, Wibowo Hardjawana, Simon Lumb, David McKechnie, Todd Essery, Branka Vucetic

Simulation results show that our approach reduces the convergence time of DDPG significantly and achieves better QoS than existing schedulers (reducing 30% ~ 50% packet losses).

Reinforcement Learning (RL) Scheduling

A Tutorial on Ultra-Reliable and Low-Latency Communications in 6G: Integrating Domain Knowledge into Deep Learning

no code implementations13 Sep 2020 Changyang She, Chengjian Sun, Zhouyou Gu, Yonghui Li, Chenyang Yang, H. Vincent Poor, Branka Vucetic

As one of the key communication scenarios in the 5th and also the 6th generation (6G) of mobile communication networks, ultra-reliable and low-latency communications (URLLC) will be central for the development of various emerging mission-critical applications.

Decision Making Decision Making Under Uncertainty

Deep Multi-Task Learning for Cooperative NOMA: System Design and Principles

no code implementations27 Jul 2020 Yuxin Lu, Peng Cheng, Zhuo Chen, Wai Ho Mow, Yonghui Li, Branka Vucetic

We develop a novel hybrid-cascaded deep neural network (DNN) architecture such that the entire system can be optimized in a holistic manner.

Multi-Task Learning

Optimizing Information Freshness in Two-Hop Status Update Systems under a Resource Constraint

no code implementations6 Jul 2020 Yifan Gu, Qian Wang, He Chen, Yonghui Li, Branka Vucetic

We derive approximate closed-form expressions of the average AoI at the destination, and the average number of forwarding operations at the relay for the DTR policy, by modelling the tangled evolution of age at relay and destination as a Markov chain (MC).

Information Theory Networking and Internet Architecture Signal Processing Information Theory

Physical Layer Authentication for Non-Coherent Massive SIMO-Enabled Industrial IoT Communications

no code implementations23 May 2020 Zhifang Gu, He Chen, Pingping Xu, Yonghui Li, Branka Vucetic

This method realizes PLA by embedding an authentication signal (tag) into a message signal, referred to as "message-based tag embedding".


Remote State Estimation with Smart Sensors over Markov Fading Channels

no code implementations16 May 2020 Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Karl Henrik Johansson, Branka Vucetic

A smart sensor forwards its local state estimate to a remote estimator over a time-correlated $M$-state Markov fading channel, where the packet drop probability is time-varying and depends on the current fading channel state.

Reconfigurable Intelligent Surface (RIS)-Enhanced Two-Way OFDM Communications

no code implementations5 May 2020 Chandan Pradhan, Ang Li, Lingyang Song, Jun Li, Branka Vucetic, Yonghui Li

In this paper, we focus on the reconfigurable intelligent surface (RIS)-enhanced two-way device-to-device (D2D) multi-pair orthogonal-frequency-division-multiplexing (OFDM) communication systems.

Vocal Bursts Valence Prediction

Deep Learning for Radio Resource Allocation with Diverse Quality-of-Service Requirements in 5G

no code implementations29 Mar 2020 Rui Dong, Changyang She, Wibowo Hardjawana, Yonghui Li, Branka Vucetic

To accommodate diverse Quality-of-Service (QoS) requirements in the 5th generation cellular networks, base stations need real-time optimization of radio resources in time-varying network conditions.

Quantization Transfer Learning

Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks

no code implementations22 Feb 2020 Changyang She, Rui Dong, Zhouyou Gu, Zhanwei Hou, Yonghui Li, Wibowo Hardjawana, Chenyang Yang, Lingyang Song, Branka Vucetic

In this article, we first summarize how to apply data-driven supervised deep learning and deep reinforcement learning in URLLC, and discuss some open problems of these methods.

Edge-computing Federated Learning +1

A Learning-Based Two-Stage Spectrum Sharing Strategy with Multiple Primary Transmit Power Levels

no code implementations21 Jul 2019 Rui Zhang, Peng Cheng, Zhuo Chen, Yonghui Li, Branka Vucetic

Then, based on a novel normalized power level alignment metric, we propose two prediction-transmission structures, namely periodic and non-periodic, for spectrum access (the second part in Stage II), which enable the secondary transmitter (ST) to closely follow the PT power level variation.

Deep Learning for Hybrid 5G Services in Mobile Edge Computing Systems: Learn from a Digital Twin

no code implementations30 Jun 2019 Rui Dong, Changyang She, Wibowo Hardjawana, Yonghui Li, Branka Vucetic

We propose a deep learning (DL) architecture, where a digital twin of the real network environment is used to train the DL algorithm off-line at a central server.

Edge-computing Management

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