MU-MIMO Uplink Timely Throughput Maximization for Extended Reality Applications

Fuente: arXiv
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Auteurs principaux: Bhagavathula, Ravi Sharan, Srinath, Pavan Koteshwar, Rial, Alvaro Valcarce, Lozano, Baltasar-Beferull
Format: Preprint
Publié: 2026
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author Bhagavathula, Ravi Sharan
Srinath, Pavan Koteshwar
Rial, Alvaro Valcarce
Lozano, Baltasar-Beferull
author_facet Bhagavathula, Ravi Sharan
Srinath, Pavan Koteshwar
Rial, Alvaro Valcarce
Lozano, Baltasar-Beferull
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2602_05751
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle MU-MIMO Uplink Timely Throughput Maximization for Extended Reality Applications
Bhagavathula, Ravi Sharan
Srinath, Pavan Koteshwar
Rial, Alvaro Valcarce
Lozano, Baltasar-Beferull
Information Theory
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.
title MU-MIMO Uplink Timely Throughput Maximization for Extended Reality Applications
topic Information Theory
url https://arxiv.org/abs/2602.05751