In this paper, we study a random access (RA) procedure to support the massive connectivity of the Internet of Things (IoT) devices, also known as the IoT connectivity. Compared with the previous RA procedures that have limitations to support the IoT connectivity due to the exponentially increased access delay, we develop an RA procedure by applying the sparse code multiple access to reduce the access delay and increase the ratio of the IoT devices that successfully complete their RA procedures. We provide the theoretical performance analysis of the proposed RA procedure with the performance metrics, such as the RA success probability, the average access delay, the RA throughput, and the average number of preamble transmissions. Then, we provide the numerical results to evaluate the performance of the proposed RA procedure based on our analysis and the ns-3 simulator. Numerical results show that our proposed RA procedure is able to support the massive connectivity requirement with improved RA performance metrics compared with the conventional RA procedures.
Bibliographical noteFunding Information:
Manuscript received February 9, 2018; revised April 20, 2018; accepted May 8, 2018. Date of publication May 14, 2018; date of current version August 9, 2018. This work was supported in part by the Institute for Information and Communications Technology Promotion through the Korea Government (MSIT) (Development on the Core Technologies of Transmission, Modulation and Coding with Low-Power and Low-Complexity for Massive Connectivity in the IoT Environment), South Korea, under Grant 2016-0-00181, and in part by the Midcareer Researcher Program through an NRF grant funded by MSIT under Grant NRF-2017R1A2 B4006908. (Corresponding author: Jang-Won Lee.) The authors are with the Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea (e-mail: firstname.lastname@example.org). Digital Object Identifier 10.1109/JIOT.2018.2835828
© 2018 IEEE.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications