Learning a decentralized medium access control protocol for shared message transmission
File(s)
Author(s)
Amorosa, Lorenzo Mario
Gao, Zhan
Verdone, Roberto
Popovski, Petar
Gündüz, Deniz
Type
Journal Article
Abstract
In large-scale Internet of things networks, efficient medium access control (MAC) is critical due to the growing number of devices competing for limited communication resources. In this work, we consider a new challenge in which a set of nodes must transmit a set of shared messages to a central controller, without inter-node communication or retransmissions. To our knowledge, this is the first work to formalize and analyze the multi-shared-message decentralized random access problem. Messages are distributed among random subsets of nodes, which must implicitly coordinate their transmissions over shared communication opportunities. The objective is to guarantee the delivery of all shared messages, regardless of which nodes transmit them. We first prove the existence of an optimal deterministic strategy, and characterize the success rate degradation of a deterministic strategy under dynamic message-transmission patterns. To solve this problem, we propose a decentralized learning-based framework that enables nodes to autonomously synthesize deterministic transmission strategies aiming to maximize message delivery success, together with an online adaptation mechanism that maintains stable performance in dynamic scenarios. Extensive simulations validate the framework’s effectiveness, scalability, and adaptability, demonstrating its robustness to varying network sizes and fast adaptation to dynamic changes in transmission patterns, outperforming state-of-the-art approaches.
Date Issued
2026-07-13
Date Acceptance
2026-07-01
Citation
IEEE Transactions on Communications, 2026
ISSN
0090-6778
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Journal / Book Title
IEEE Transactions on Communications
Copyright Statement
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
License URL
Publication Status
Published online
Date Publish Online
2026-07-13