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Resource-aware relay selection for inter-cell interference avoidance in 5G heterogeneous network for Internet of Things systems

Authors
Dao, N.-N.Park, M.Kim, J.Paek, J.Cho, S.
Issue Date
Apr-2019
Publisher
Elsevier B.V.
Keywords
Internet of Things; 5G heterogeneous network; Inter-cell interference; Network resource availability; Device-to-device communication
Citation
Future Generation Computer Systems, v.93, pp 877 - 887
Pages
11
Journal Title
Future Generation Computer Systems
Volume
93
Start Page
877
End Page
887
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/3275
DOI
10.1016/j.future.2018.03.037
ISSN
0167-739X
1872-7115
Abstract
The fifth-generation (5G) heterogeneous networks (HetNets) are gaining attention to be a key enabler that provides promising infrastructure for the massive proliferation of Internet of Things (IoT) devices and their services. However, one of the key challenges that the IoT terminals face is the inter-cell interference (ICI) problem since the 5G HetNets are generally deployed based on a co-channel model that overlays numerous pico eNodeBs (eNBs) on top of macro eNBs grid on the same frequency band. In order to overcome the ICI problem, we propose a relay-assisted communication approach by which the data of interfered IoT terminal (iIT) in the ICI area is relayed, via a device-to-device connection, to its neighboring IoT terminals which has good signal to and from the network. The key component in this proposed scheme is the relay selection algorithm which aims at maximizing the network resource availability at the highest priority, as well as device data rate. Firstly, resource availability maximization (RAmax) function determines an eNB that has maximum resource availability among all neighboring eNBs of the iIT to be a gateway node for the relay connection to the network (referred to as reNB). Among the IoT terminals associated with the reNB, a relay IoT terminal (called rIT) linking iIT and reNB is selected by a condition of maximum channel quality to the reNB. Simulation results show that our proposed algorithm increases total network throughput and the number of simultaneously served ITs by 44% and 20%, respectively. © 2018 Elsevier B.V.
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소프트웨어대학 (소프트웨어학부)
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