Branka Vucetic

Policy-Guided MCTS for near Maximum-Likelihood Decoding of Short Codes

Yu Tian, C. Patrick Yue, Peiyao Cheng, Gaoyang Pang et autres

In this paper, we propose a policy-guided Monte Carlo Tree Search (MCTS) decoder that achieves near maximum-likelihood decoding (MLD) performance for short block codes. The MCTS decoder searches for test error patterns (TEPs) in the received information bits and obtains codeword candidates …

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Graph Neural Network-Based End-to-End Learning for Multi-User MIMO Systems

Hao Chang, Hoang Triet Vo, Alva Kosasih, Branka Vucetic et autres

End-to-end (E2E) learning has recently been proposed to jointly design the modulator and symbol detector by using deep neural networks (DNNs). However, existing schemes lack sufficient capability to cancel multi-user interference (MUI) in uplink multi-user multiple-input multiple-output (MU-MIMO) systems. In this paper, …

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A novel K-GWO-SVM algorithm for the analysis of ECG signals

Ghazal Tafti, Zihuai Lin, Branka Vucetic, Ming Ding et autres

This paper presents a robust yet efficient Grey Wolf Optimizer-Support Vector Machine algorithm, termed K-GWO-SVM, for the analysis of ECG signals in smart healthcare systems, aiming to improve classification accuracy and computational efficiency. The proposed model introduces three main contributions: (1) the …

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A Tchebycheff-Guided MARL-Based Channel Access in IEEE 802.11ah Networks

Tian Qiu, Litianyi Zhang, Peng Cheng, Shenghong Li et autres

This paper addresses the challenge of balancing per-station throughput and overall fairness for IEEE 802.11ah uplink scenarios with heterogeneous link conditions and shared-medium contention. We propose a learning-based MAC-layer enhancement that replaces the backoff mechanism with a policy-driven transmission decision, enabling explicit …

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Toward Wireless Human-Machine Collaboration in the 6G Era

Gaoyang Pang, Wanchun Liu, Chentao Yue, Daniel E. Quevedo et autres

The next industrial revolution, Industry 5.0, will be driven by advanced technologies that foster human-machine collaboration (HMC). It will leverage human creativity, judgment, and dexterity with the machine's strength, precision, and speed to improve productivity, quality of life, and sustainability. Wireless communications, …

Toward Wireless Human-Machine Collaboration in the 6G Era

Gaoyang Pang, Wanchun Liu, Chentao Yue, Daniel E. Quevedo et autres

The next industrial revolution, Industry 5.0, will be driven by advanced technologies that foster human-machine collaboration (HMC). It will leverage human creativity, judgment, and dexterity with the machine's strength, precision, and speed to improve productivity, quality of life, and sustainability. Wireless communications, …

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LocDreamer: World Model-Based Learning for Joint Indoor Tracking and Anchor Scheduling

Geng Wang, Zhouyou Gu, Shenghong Li, Peng cheng et autres

Accurate, resource-efficient localization and tracking enables numerous location-aware services in next-generation wireless networks. However, existing machine learning-based methods often require large labeled datasets while overlooking spectrum and energy efficiencies. To fill this gap, we propose LocDreamer, a world model (WM)-based framework for …

LocDreamer: World Model-Based Learning for Joint Indoor Tracking and Anchor Scheduling

Geng Wang, Zhouyou Gu, Shenghong Li, Peng cheng et autres

Accurate, resource-efficient localization and tracking enables numerous location-aware services in next-generation wireless networks. However, existing machine learning-based methods often require large labeled datasets while overlooking spectrum and energy efficiencies. To fill this gap, we propose LocDreamer, a world model (WM)-based framework for …

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Hybrid Centralized Distributed Control for Lifelong MAPF over Wireless Connections

Jinghao Cao, Wanchun Liu, Yonghui Li, Branka Vucetic

In lifelong multi-agent path finding (MAPF) with many robots, unreliable wireless links and stochastic executions are the norm. Existing approaches typically either rely on centralized planning under idealized communication, or run fully distributed local controllers with fixed communication patterns; they rarely couple …

Hybrid Centralized Distributed Control for Lifelong MAPF over Wireless Connections

Jinghao Cao, Wanchun Liu, Yonghui Li, Branka Vucetic

In lifelong multi-agent path finding (MAPF) with many robots, unreliable wireless links and stochastic executions are the norm. Existing approaches typically either rely on centralized planning under idealized communication, or run fully distributed local controllers with fixed communication patterns; they rarely couple …

SIG-SDP: Sparse Interference Graph-Aided Semidefinite Programming for Large-Scale Wireless Time-Sensitive Networking

Zhouyou Gu, Jihong Park, Branka Vucetic, Jinho D. Choi

Wireless time-sensitive networking (WTSN) is essential for Industrial Internet of Things. We address the problem of minimizing time slots needed for WTSN transmissions while ensuring reliability subject to interference constraints—an NP-hard task. Existing semidefinite programming (SDP) methods can relax and solve the …

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Label-Free Range-Based Indoor Tracking With Physics-Guided Deep State Space Model

Geng Wang, Peng Cheng, S. Li, Wei Xiang et autres

Accurate indoor tracking is essential to modern location-based services, fundamentally transforming the way we interact with indoor environments. Traditional state space model (SSM)-based tracking approaches often exhibit limitations in complex environments due to their reliance on fixed and overly simplifiedtransitionandobservationfunctions, which restricts …

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