학술논문

On Error Probability Analysis of Short-Packet Communications in Massive Internet of Things
Document Type
Periodical
Source
IEEE Access Access, IEEE. 12:67107-67116 2024
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Error probability
Internet of Things
Interference
Probability density function
Geometry
Signal to noise ratio
Nakagami distribution
Stochastic processes
Stochastic geometry
short-packet communication
slotted ALOHA
finite block-length
Language
ISSN
2169-3536
Abstract
In this paper, we present a novel reliability analysis of massive Internet of Things (IoT) connectivity in cellular networks. In massive IoT networks, IoT devices sporadically and unpredictably send short data packets to nearby base stations (BSs), potentially interfering with other IoT devices with whom they share the uplink channel. Assuming slotted ALOHA random access policy, we investigate the probability that an IoT device transmitting a short data packet is not decoded at the nearest BS under Nakagami fading. We derive error probability expressions combining the tools of finite block-length (FBL) information theory and stochastic geometry. Derived FBL-based results are confirmed by Monte Carlo simulations and further compared with the asymptotic expressions available in the previous studies that are obtained under assumption that a device transmits asymptotically long data packets. Numerical results confirm the accuracy of the obtained expressions and their applicability to the massive IoT system design and performance evaluation under a wide range of system parameters. For example, the matching between the values obtained by numerical integration and approximation results of the FBL error probability is in the range between 97.6-99.4 % for different choices of the parameters.