Open AccessMulti‐objective optimisation for heterogeneous cellular network planning
Author(s) -
Tseng FanHsun,
Chen ChiYuan,
Chao HanChieh
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5332
Subject(s) - macrocell , computer science , network planning and design , cellular network , capacity planning , heterogeneous network , network resource planning , homogeneous , scale (ratio) , wireless network , genetic algorithm , function (biology) , mathematical optimization , computer network , distributed computing , wireless , base station , telecommunications , machine learning , mathematics , biology , operating system , combinatorics , quantum mechanics , evolutionary biology , physics
Small cell aims at improving the cell coverage and capacity of macrocell. Network operators investigate cell planning for improving system performance and for satisfying user requirements with minimal construction cost and least unserved users. Most of the existing literature merely considered a single objective function or investigated cell planning for small‐scale and homogeneous networks. This study aims to optimise multiple objective functions of a large‐scale and heterogeneous wireless network with multiple macrocells and multiple small cells. The authors formulate the multi‐objective optimisation problem of cell planning for heterogeneous cellular networks. The three objects include construction cost, number of unserved users and network capacity. Then they propose the large‐scale cell planning genetic algorithm (LSCPGA) to find a planning result with the lowest fitness value. Simulation results show that LSCPGA economises 9–20% construction cost, eliminates the number of unserved users from 4 to 10% and enhances 2–15% in network capacity compared to other planning algorithms.