Timeliness of CSMA/CA-Based Wireless Networks With HARQ in the FBL Regime: Explicit Age Characterizations and Resource Allocation

In this article, we consider an Industrial Internet of Things (IIoT) network operating under a carrier sense multiple access with collision avoidance (CSMA/CA) protocol. Latency-sensitive packets generated at multiple stations randomly are transmitted to a destination for decision making. To meet the strict timeliness constraint, the transmissions are carried by finite blocklength (FBL) codes, while the truncated hybrid automatic repeat request (HARQ) scheme is exploited to improve the reliability. For such unsaturated CSMA/CA networks, for the first time, we characterize the timeliness of packets utilized for decision-making via the age upon decisions (AuD) metric which emphasizes the information freshness at decision moments in comparison to age of information (AoI). To explicitly quantify the AuD performance, we develop an equivalent and tractable unsaturated Markov transfer model for the considered network and investigate the transmission probability and collision probability, respectively. Subsequently, the probability density functions of interarrival time and service time of the successfully transmitted packets are derived. We further derive a closed-form expression for the average AuD under a geometric decision process accordingly. Based on these characterizations, we aim at improving average AuD by jointly allocating the blocklength and transmit power. The formulated nonconvex problem is decomposed into subproblems, and we prove its joint convexity across all feasible intervals. Via simulations, we evaluate the performance of the considered network and conclude a series of design guidelines.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-03-24
DOI
https://doi.org/10.1109/jiot.2025.3554242
Primary Topic
Age of Information Optimization
Type
article
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article

Timeliness of CSMA/CA-Based Wireless Networks With HARQ in the FBL Regime: Explicit Age Characterizations and Resource Allocation

Yunquan Dong, James Gross, Ming Gan, Yulin Hu et al.
IEEE Internet of Things Journal
Age of Information Optimization
article

Timeliness of CSMA/CA-Based Wireless Networks With HARQ in the FBL Regime: Explicit Age Characterizations and Resource Allocation

Yunquan Dong, James Gross, Ming Gan, Yulin Hu, Zhiwei Bao
article en

Abstract

In this article, we consider an Industrial Internet of Things (IIoT) network operating under a carrier sense multiple access with collision avoidance (CSMA/CA) protocol. Latency-sensitive packets generated at multiple stations randomly are transmitted to a destination for decision making. To meet the strict timeliness constraint, the transmissions are carried by finite blocklength (FBL) codes, while the truncated hybrid automatic repeat request (HARQ) scheme is exploited to improve the reliability. For such unsaturated CSMA/CA networks, for the first time, we characterize the timeliness of packets utilized for decision-making via the age upon decisions (AuD) metric which emphasizes the information freshness at decision moments in comparison to age of information (AoI). To explicitly quantify the AuD performance, we develop an equivalent and tractable unsaturated Markov transfer model for the considered network and investigate the transmission probability and collision probability, respectively. Subsequently, the probability density functions of interarrival time and service time of the successfully transmitted packets are derived. We further derive a closed-form expression for the average AuD under a geometric decision process accordingly. Based on these characterizations, we aim at improving average AuD by jointly allocating the blocklength and transmit power. The formulated nonconvex problem is decomposed into subproblems, and we prove its joint convexity across all feasible intervals. Via simulations, we evaluate the performance of the considered network and conclude a series of design guidelines.

IEEE Internet of Things JournalVol. 12(13)
Nanjing University of Information Science and Technology (CN), Huawei Technologies (China) (CN), Wuhan University (CN), KTH Royal Institute of Technology (SE)
Decent work and economic growth
Openalex Percentile: Top 95%
Age of Information Optimization
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