Table of Contents Author Guidelines Submit a Manuscript
Wireless Communications and Mobile Computing
Volume 2017, Article ID 8086204, 25 pages
Research Article

Fuzzy Logic Based Coverage and Cost Effective Placement of Serving Nodes for 4G and Beyond Cellular Networks

1School of Electronics Engineering, VIT University, Vellore, Tamil Nadu, India
2School of Electrical Engineering, VIT University, Vellore, Tamil Nadu, India

Correspondence should be addressed to Arthi Murugadass; moc.liamg@sadmihtra

Received 14 July 2016; Revised 13 October 2016; Accepted 23 October 2016; Published 16 January 2017

Academic Editor: Giovanni Pau

Copyright © 2017 Arthi Murugadass and Arulmozhivarman Pachiyappan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The densification of serving nodes is one of the potential solutions to maximize the spectral efficiency per unit area. This is preposterous on account of conventional base stations (BS) for which site procurement is costly. Long term evolution-advanced (LTE-A) defines the idea of heterogeneous networks (HetNets), where BSs with different coverage and capacity are utilized to guarantee the quality of service (QoS) requirements of the clients. To maximize the transmission quality of the clients in the coverage holes, LTE-A also defines multihop relay (MHR) networks, where the relay stations (RSs) are also placed along with the BSs. Unfortunately, the placement approaches for HetNet and MHR serving nodes are not standardized. In this work, two different approaches like site selection with maximum service coverage (SSMSC) and site selection with minimum placement cost (SSMPC) are proposed, which identifies the required number of serving nodes, their types, and the placement locations to maximize the coverage and to maintain the placement cost (PC) within the limits of the total placement budget. The simulation results demonstrate that the proposed approaches are computationally less complex and offer enhanced performance in terms of aggregate PC, coverage, and power proportion compared to the other conventional approaches.