A Multi-objective Design of In-Building Distributed Antenna System Using Evolutionary Algorithms

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2 Scopus citations

Abstract

The increasing data traffic inside buildings requires maintaining good cellular network coverage for indoor mobile users. Passive In-building Distributed Antenna System (IB-DAS) is one of the most efficient methods to provide an indoor solution that meets the signal strength requirements. It is a network of spatially distributed antennas in a building connected to telephone rooms which are then connected to a Base Transmission Station (BTS). These connections are established through passive coaxial cables and splitters. The design of IB-DAS is considered to be challenging due to the power-sharing property resulting in two contradicting objectives: minimizing the power usage at the BTS (long-term cost) and minimizing the design components cost (short-term cost). Different attempts have been made in the literature to solve this problem. Some of them are either lacking the consideration of all necessary aspects or facing scalability issues. Additionally, most of these attempts translate the IB-DAS design into a mono-objective problem, which leads to a challenging task of determining a correct combined objective function with justified weighting factors associated with each objective. Moreover, these approaches do not produce multiple design choices which may not be satisfactory in practical scenarios. In this paper, we propose a multi-objective algorithm for designing IB-DAS. The experimental results show the success of this algorithm to achieve our industrial partner’s requirement of providing different design options that cannot be achieved using mono-objective approaches.

Original languageBritish English
Title of host publicationArtificial Intelligence XXXVI - 39th SGAI International Conference on Artificial Intelligence, AI 2019, Proceedings
EditorsMax Bramer, Miltos Petridis
PublisherSpringer
Pages253-266
Number of pages14
ISBN (Print)9783030348847
DOIs
StatePublished - 2019
Event39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2019 - Cambridge, United Kingdom
Duration: 17 Dec 201919 Dec 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11927 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2019
Country/TerritoryUnited Kingdom
CityCambridge
Period17/12/1919/12/19

Keywords

  • Crowding distance
  • Distributed Antenna System
  • Multi-objective evolutionary algorithm
  • Non-dominated Sorting Genetic Algorithm
  • Normalization

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