Throughput Analysis of Low-Latency IoT Systems with QoS Constraints and Finite Blocklength Codes


Y. Hu, Y. Li, M. C. Gursoy, S. Velipasalar, A. Schmeink,


        Internet of Things (IoT) is a promising paradigm to connect massive number of devices in future wireless communications while satisfying various quality of service (QoS) requirements. In this paper, we consider a QoS-constrained IoT system operating with finite blocklength (FBL) codes to support low latency communications. Two data arrival models are considered, namely, constant-rate arrival and ON-OFF discrete-time Markov arrival. The throughput performance is studied for both arrival models under statistical queuing constraints and deadline limits.For the scenario with instantaneous channel state information (CSI), we derive the QoS-constrained throughput expressions for both arrival models. Subsequently, an instantaneous CSI-driven optimal power control algorithm is proposed to maximize the throughput, while guaranteeing a certain reliability target. In addition, we consider a scenario with only average CSI being available at the transmitter and propose to apply hybrid automatic repeat request (HARQ) schemes to improve the FBL performance. The decoding error probability and the outage probability are first characterized, following which the distribution of transmission period is derived. Furthermore, the throughput expressions are provided for both types of arrivals. Via numerical analysis, the impact of error probability, fixed transmission rate, coding blocklength, and QoS constraints on the throughput is studied.


Finite blocklength, HARQ, internet of things (IoT), markov arrivals, power control, QoS

BibTEX Reference Entry 

	author = {Yulin Hu and Yi Li and M. Cenk Gursoy and Senem Velipasalar and Anke Schmeink},
	title = "Throughput Analysis of Low-Latency IoT Systems with {QoS} Constraints and Finite Blocklength Codes",
	pages = "1-17",
	journal = "Transactions on Vehicular Technology",
	volume = "69",
	number = "3",
	doi = 10.1109/TVT.2020.2968463,
	month = Mar,
	year = 2020,
	hsb = RWTH-2021-08229,


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