Network State Sensing-Assisted Resource Allocation for Grant-Free Multiple Access With Users of Heterogeneous Delay Tolerance

In the design of grant-free multiple access (GFMA) mechanisms, accurate estimation of the number of active user equipments (UEs) is critical to guarantee effective access performance for different UEs with heterogeneous delay tolerance. This is particularly vital in practical complex scenarios where high-mobility and low-mobility UEs coexist, as the reliability of transmission can also directly impact the access performance of UEs. In this paper, we propose a network state sensing-assisted multiple access with dynamic resource allocation scheme that enables both delay-sensitive unmanned aerial vehicles (UAVs) and delay-tolerant terrestrial UEs to access the base station (BS) simultaneously. Taking into account the limited radio resources and the practical assumption that the number of active UEs is not available at the BS, we develop a network state sensing-assisted dynamic resource allocation algorithm that can accurately determine the number of active UEs in real-time and judiciously allocate the limited radio resources according to the active number of UAVs and terrestrial UEs, as well as their corresponding priorities. Additionally, we dynamically adapt the access class barring factors to satisfy the heterogeneous access delay requirement of UEs. Through numerical results, we demonstrate that our proposed scheme outperforms baseline methods in terms of both access delay and throughput. Furthermore, it achieves comparable performance to that of an ideal algorithm, which assumes perfect information on the number of active UEs is available.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-07-14
DOI
https://doi.org/10.1109/tvt.2025.3588872
Citations
5
Primary Topic
Age of Information Optimization
Type
article
Field-Weighted Citation Impact
7.44
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article

Network State Sensing-Assisted Resource Allocation for Grant-Free Multiple Access With Users of Heterogeneous Delay Tolerance

Bin Cao, Derrick Wing Kwan Ng, Mugen Peng, Yuanwei Liu et al.
5 citations
IEEE Transactions on Vehicular Technology
Age of Information Optimization
7.44
article

Network State Sensing-Assisted Resource Allocation for Grant-Free Multiple Access With Users of Heterogeneous Delay Tolerance

Bin Cao, Derrick Wing Kwan Ng, Mugen Peng, Yuanwei Liu, Chenxi Liu, Xiaoling Hu, Liujie Li
article en
5 citations

Abstract

In the design of grant-free multiple access (GFMA) mechanisms, accurate estimation of the number of active user equipments (UEs) is critical to guarantee effective access performance for different UEs with heterogeneous delay tolerance. This is particularly vital in practical complex scenarios where high-mobility and low-mobility UEs coexist, as the reliability of transmission can also directly impact the access performance of UEs. In this paper, we propose a network state sensing-assisted multiple access with dynamic resource allocation scheme that enables both delay-sensitive unmanned aerial vehicles (UAVs) and delay-tolerant terrestrial UEs to access the base station (BS) simultaneously. Taking into account the limited radio resources and the practical assumption that the number of active UEs is not available at the BS, we develop a network state sensing-assisted dynamic resource allocation algorithm that can accurately determine the number of active UEs in real-time and judiciously allocate the limited radio resources according to the active number of UAVs and terrestrial UEs, as well as their corresponding priorities. Additionally, we dynamically adapt the access class barring factors to satisfy the heterogeneous access delay requirement of UEs. Through numerical results, we demonstrate that our proposed scheme outperforms baseline methods in terms of both access delay and throughput. Furthermore, it achieves comparable performance to that of an ideal algorithm, which assumes perfect information on the number of active UEs is available.

IEEE Transactions on Vehicular TechnologyVol. 74(12)
Beijing University of Posts and Telecommunications (CN), UNSW Sydney (AU), University of Hong Kong (HK)
Openalex Percentile: Top 3%
Age of Information Optimization
7.44
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