Title

Distributed Gateway Selection for M2M Communication in Cognitive 5G Networks

Document Type

Article

Publication Date

11-1-2017

Publication Title

IEEE Networks

DOI

10.1109/MNET.2017.1700017

ISSN

1558-156X

Abstract

M2M communication is an important component for future wireless networks. M2M systems consist of a large number of devices that can operate with minimum or no human intervention. However, spectrum demand rises exponentially with the increase in the number of connected devices. Cognitive 5G networks are key to address the issue of spectrum scarcity. Further, use of multiple gateways in cognitive 5G networks for M2M communication can increase system throughput, coverage, and energy efficiency. Nevertheless, using multiple gateways for the secondary M2M devices may cause interference to the primary M2M devices. Existing gateway selection protocols for cognitive M2M communication mostly use single channel CSMA, and thus are not efficient in terms of reducing the interference. Thus, in this article, we propose a DGAP based on multi-channel CSMA for M2M communication in 5G networks. Further, we propose a Lo-DGAP, where each gateway transmits only the worst primary M2M device information rather than transmitting all neighboring primary M2M device information. The proposed Lo-DGAP increases the throughput of the system by reducing the message header payload and is also energy- efficient. Simulation results demonstrate the effectiveness of the proposed schemes in terms of network lifetime and energy consumption.

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