A clustering algorithm that maximizes throughput in 5G heterogeneous F-RAN networks

Date

2018-07-27

Author

Balevi, Eren
Gitlin, Richard D.

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

103
views

0
downloads

© 2018 IEEE.In this paper, a clustering algorithm is proposed that dynamically determines the locations of fog nodes in 5G wireless networks, which are upgraded from small cells, in order to maximize throughput assuming the number of fog nodes and small cells are given as a priori information. The proposed algorithm dynamically clusters the small cells around the fog nodes. The approach is based on a soft clustering model where one small cell can be connected to many fog nodes. The numerical results demonstrate that the proposed clustering algorithm significantly enhances the throughput and lowers the latency with respect to the distance-based K- means hard clustering algorithm or Voronoi tessellation model.

Subject Keywords

Clustering, Fog computing, HetNets

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051445028&origin=inward
https://hdl.handle.net/11511/100203

DOI

https://doi.org/10.1109/icc.2018.8422151

Conference Name

2018 IEEE International Conference on Communications, ICC 2018

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

A novel deep reinforcement learning algorithm for online antenna tuning Balevi, Eren; Andrews, Jeffrey G. (2019-12-01) © 2019 IEEE.The interactions between the cells, most notably due to their coupled interference and the large number of users, render the optimization of antenna parameters prohibitively complex. To cope with this problem, we propose a novel practical deep learning (DL) based reinforcement learning (RL) algorithm to jointly optimize antenna tilt angle and vertical and horizontal half-power beamwidths of the macrocells in a heterogeneous cellular network (HetNet). In the proposed algorithm, DL is used to extr...
A Distributed Fault-Tolerant Topology Control Algorithm for Heterogeneous Wireless Sensor Networks Bagci, Hakki; KÖRPEOĞLU, İBRAHİM; Yazıcı, Adnan (Institute of Electrical and Electronics Engineers (IEEE), 2015-04-01) This paper introduces a distributed fault-tolerant topology control algorithm, called the Disjoint Path Vector (DPV), for heterogeneous wireless sensor networks composed of a large number of sensor nodes with limited energy and computing capability and several supernodes with unlimited energy resources. The DPV algorithm addresses the k-degree Anycast Topology Control problem where the main objective is to assign each sensor's transmission range such that each has at least k-vertex-disjoint paths to superno...
Unsupervised machine learning in 5G networks for low latency communications Balevi, Eren; Gitlin, Richard D. (2018-02-02) © 2017 IEEE.This paper incorporates fog networking into heterogeneous cellular networks that are composed of a high power node (HPN) and many low power nodes (LPNs). The locations of the fog nodes that are upgraded from LPNs are specified by modifying the unsupervised soft-clustering machine learning algorithm with the ultimate aim of reducing latency. The clusters are constructed accordingly so that the leader of each cluster becomes a fog node. The proposed approach significantly reduces the latency with ...
A Greedy Link Scheduler for Wireless Networks with Gaussian Multiple Access and Broadcast Channels Sridharan, Arun; Koksal, C. Emre; Uysal, Elif (2010-03-19) Information theoretic Broadcast Channels (BC) and Multiple Access Channels (MAC) enable a single node to transmit data simultaneously to multiple nodes, and multiple nodes to transmit data simultaneously to a single node respectively. In this paper, we address the problem of link scheduling in multihop wireless networks containing nodes with BC and MAC capabilities. We first propose an interference model that extends protocol interference models, originally designed for point to point channels, to include t...
A METHOD FOR COMPARATIVE-EVALUATION OF EIT ALGORITHMS USING A STANDARD DATA SET IDER, YZ; EYUBOGLU, BM; KUZUOGLU, M; Leblebicioğlu, Mehmet Kemal; BAYSAL, U; CAGLAR, BK; BIRGUL, O (IOP Publishing, 1995-08-01) The point spread function (PSF) is the most widely used tool for quantifying the spatial resolution of imaging systems. However, prerequisites for the proper use of this tool are linearity and space invariance. Because EIT is non-linear it is only possible to compare different reconstruction algorithms using a standard data set. In this study, the FEM is used to generate simulation data, which are used to investigate the non-linear behaviour of EIT, the space dependence of its PSF and its capability of reso...

Citation Formats

E. Balevi and R. D. Gitlin, “A clustering algorithm that maximizes throughput in 5G heterogeneous F-RAN networks,” Missouri, Amerika Birleşik Devletleri, 2018, vol. 2018-May, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051445028&origin=inward.