Greedy-Based Scheduler for Multiuser Space–Time Line Coded Systems

This study proposes a low-complexity, greedy-based scheduler for multiuser space–time line coded (MU-STLC) systems. The proposed scheduler selects one user that was unscheduled in the previous scheduling period and replaces it with the currently scheduled user with minimum proportional fair priority to maximize the sum priority of the scheduled users. Consequently, the proposed greedy-based scheduler can significantly reduce computational complexity compared to existing schedulers. Furthermore, a novel low-complexity matrix inversion (LMI) algorithm has been devised to further decrease computational complexity by leveraging the order-recursive structure of the MU-STLC preprocessing matrix. Simulation results confirm that the greedy-based scheduler utilizing the LMI algorithm significantly reduces the computational complexity of existing schedulers, albeit with a slight degradation in scheduling performance.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-10-02
DOI
https://doi.org/10.1109/tvt.2025.3617079
Primary Topic
Advanced Wireless Network Optimization
Type
article
Field-Weighted Citation Impact
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article

Greedy-Based Scheduler for Multiuser Space–Time Line Coded Systems

Chau Yuen, Jingon Joung, Jihoon Choi, Jaehong Kim et al.
IEEE Transactions on Vehicular Technology
Advanced Wireless Network Optimization
article

Greedy-Based Scheduler for Multiuser Space–Time Line Coded Systems

Chau Yuen, Jingon Joung, Jihoon Choi, Jaehong Kim, Han-Gyeol Lee
article en

Abstract

This study proposes a low-complexity, greedy-based scheduler for multiuser space–time line coded (MU-STLC) systems. The proposed scheduler selects one user that was unscheduled in the previous scheduling period and replaces it with the currently scheduled user with minimum proportional fair priority to maximize the sum priority of the scheduled users. Consequently, the proposed greedy-based scheduler can significantly reduce computational complexity compared to existing schedulers. Furthermore, a novel low-complexity matrix inversion (LMI) algorithm has been devised to further decrease computational complexity by leveraging the order-recursive structure of the MU-STLC preprocessing matrix. Simulation results confirm that the greedy-based scheduler utilizing the LMI algorithm significantly reduces the computational complexity of existing schedulers, albeit with a slight degradation in scheduling performance.

IEEE Transactions on Vehicular Technology
Nanyang Technological University (SG), Korea Aerospace University (KR), Chung-Ang University (KR)
Openalex Percentile: Top 73%
Advanced Wireless Network Optimization
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