MU-MIMO Uplink Timely Throughput Maximization for Extended Reality Applications

Ravi Sharan Bhagavathula; Pavan Koteshwar Srinath; Alvaro Valcarce Rial; Baltasar-Beferull Lozano

MU-MIMO Uplink Timely Throughput Maximization for Extended Reality Applications

Information Theory 2026-02-06 v1 math.IT

Authors: Ravi Sharan Bhagavathula , Pavan Koteshwar Srinath , Alvaro Valcarce Rial , Baltasar-Beferull Lozano

Abstract

In this work, we study the cross-layer timely throughput maximization for extended reality (XR) applications through uplink multi-user MIMO (MU-MIMO) scheduling. Timely scheduling opportunities are characterized by the peak age of information (PAoI)-metric and are incorporated into a network-side optimization problem as constraints modeling user satisfaction. The problem being NP-hard, we resort to a signaling-free, weighted proportional fair-based iterative heuristic algorithm, where the weights are derived with respect to the PAoI metric. Extensive numerical simulation results demonstrate that the proposed algorithm consistently outperforms existing baselines in terms of XR capacity without sacrificing the overall system throughput.

Keywords

mimo communication hyperparameter optimization network protocol

Cite

@article{arxiv.2602.05751,
  title  = {MU-MIMO Uplink Timely Throughput Maximization for Extended Reality Applications},
  author = {Ravi Sharan Bhagavathula and Pavan Koteshwar Srinath and Alvaro Valcarce Rial and Baltasar-Beferull Lozano},
  journal= {arXiv preprint arXiv:2602.05751},
  year   = {2026}
}

Comments

14 pages, single column, 4 figures. This work has been submitted to the IEEE for possible publication

MU-MIMO Uplink Timely Throughput Maximization for Extended Reality Applications

Abstract

Keywords

Cite

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