Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/62923
Title: | Radio resource allocation for D2D-enabled massive machine communication in the 5G era |
Contributor(s): | Yang, Huitao (author); Seet, Boon-Chong (author); Hasan, Syed Faraz (author) ; Chong, Peter Han Joo (author); Chung, Min Young (author) |
Publication Date: | 2016 |
DOI: | 10.1109/DASC-PICom-DataCom-CyberSciTec.2016.24 |
Handle Link: | https://hdl.handle.net/1959.11/62923 |
Abstract: | | Device-to-Device (D2D) and Massive Machine Communication (MMC) are believed to be the cornerstones of future 5th generation (5G) cellular technologies. As a method to increase spectrum utilization, extend cellular coverage, and offload backhaul traffic, D2D has been recently incorporated into Release 12 of 3rd Generation Partnership Project (3GPP) Long Term Evolution Advanced (LTE-A) specifications. Devices in physical proximity can thus discover each other and communicate via a direct path using licensed LTE spectrums. Leveraging on the ubiquity of cellular coverage and harnessing LTE-A D2D for networks with massive number of machine-type communications, such as large-scale sensor networks and vehicular networks, introduces a paradigm shift and opens up new opportunities for proximity-based services. In this paper, we propose a novel radio resource allocation method for D2D discovery in clustered MMC networks. With a large number of nodes, the proposed method can still maintain the signaling overhead at a reasonable level while achieving high discovery rate. Experimental results show that the proposed approach significantly outperforms the existing 3GPP random resource allocation mechanism.
Publication Type: | Conference Publication |
Conference Details: | 8th - 12th August, 2016 |
Source of Publication: | Proceedings of the IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress, DASC/PiCom/DataCom/CyberSciTech 2016, p. 55-60 |
Publisher: | Institute of Electrical and Electronics Engineers |
Place of Publication: | United States of America |
Fields of Research (FoR) 2020: | 4006 Communications engineering |
Socio-Economic Objective (SEO) 2020: | tbd |
Peer Reviewed: | Yes |
HERDC Category Description: | E1 Refereed Scholarly Conference Publication |
Appears in Collections: | Conference Publication
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