In this paper, two-stage random-access-based massive Internet-of-things uplink transmission is investigated. In this scheme, aggregator nodes are additionally deployed to relay packets to deal with a massive number of arrivals. A user node determines whether to utilize aggregator nodes according to the received signal strength from base stations and aggregator nodes. If the user node selects and transmits a packet to an aggregator node, the aggregator node stores and forwards the received packet to the base station. The use of aggregator nodes can reduce the per-hop delay as well as the user energy consumption by reducing the transmission distance from user nodes. However, in the two-stage random access protocol, an increase in the number of aggregator nodes incurs collisions in the wireless medium, and hence, increases the queueing delay at the aggregator node. Thus, improved radio resource allocation and network design are required to reduce additional delay in the two-hop uplink system. We, therefore, focus on optimizing the transmission probabilities of transmitting nodes and the aggregator node density to minimize the delay in two-stage random access networks.
Bibliographical noteFunding Information:
Manuscript received March 18, 2016; revised December 28, 2016, May 8, 2017, and August 24, 2017; accepted November 6, 2017. Date of publication November 23, 2017; date of current version April 16, 2018. This work was supported by a grant to Bio-Mimetic Robot Research Center Funded by Defense Acquisition Program Administration, and by the Agency for Defense Development (UD160027ID). The review of this paper was coordinated by Prof. Nei Kato. (Corresponding author: Jeemin Kim) J. Kim and S.-L. Kim are with the Radio Resource Management and Optimization, School of Electrical and Electronic Engineering, Yonsei University, seoul 03722, Korea (e-mail: firstname.lastname@example.org; slkim@ ramo.yonsei.ac.kr).
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All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Aerospace Engineering
- Electrical and Electronic Engineering
- Applied Mathematics