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Open AccessArticle

5G Base Station Deployment Perspectives in Millimeter Wave Frequencies Using Meta-Heuristic Algorithms

1
School of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
2
School of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ 07030, USA
3
School of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(11), 1318; https://doi.org/10.3390/electronics8111318
Received: 20 September 2019 / Revised: 24 October 2019 / Accepted: 6 November 2019 / Published: 8 November 2019
(This article belongs to the Section Microwave and Wireless Communications)
It can be predicted that the infrastructure of the existing wireless networks will not fill the requirement of the fifth generation (5G) wireless network due to the high data rates and a large number of expected traffic. Thus, a novel deployment method is crucial to satisfy 5G features. Meta-heuristic is expected to be a promising method for the complex deployment optimization problem of the 5G network. This work presents an implementation of a meta-heuristic algorithm based on swarm intelligence, to minimize the number of base stations (BSs) and optimize their placements in millimeter wave (mmWave) frequencies (e.g., 28 GHz and 38 GHz) in the context of the 5G network while satisfying user data rates requirement. Then, an iterative method is applied to remove redundant BSs. We formulate an optimization problem that takes into account multiple 5G network deployment scenarios. Further, a comparative study is conducted with the well-known simulated annealing (SA) using Monte Carlo simulations to assess the performance of the developed model. In our simulation results, we divide the region of interest into two subareas with different user distributions for different network scenarios while considering the intercell interference. The results demonstrate that the proposed approach has better network coverage with low percentage users in outage. In addition, the developed approach has less computational times to reach the desired target network quality of service (QoS). View Full-Text
Keywords: 5G network planning; millimeter wave; base stations; meta-heuristic algorithms 5G network planning; millimeter wave; base stations; meta-heuristic algorithms
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Ganame, H.; Yingzhuang, L.; Ghazzai, H.; Kamissoko, D. 5G Base Station Deployment Perspectives in Millimeter Wave Frequencies Using Meta-Heuristic Algorithms. Electronics 2019, 8, 1318.

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