Multi‐objective optimisation for heterogeneous cellular network planning

Abstract

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.