Comparison of Multiobjective Optimal and Collocated 4G and 5G Small Cells Using Street Lampposts as Candidate Locations

Biruk E. Tegicho, Beneyam B. Haile, Edward Mutafungwa, Jyri Hamalainen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

To address the increasing capacity demand due to adoption of data-intensive services and broadband devices, densification of mobile networks by small cell deployments has been considered as one key systematic solution for both legacy fourth generation (4G) mobile networks and future fifth generation (5G) network upgrades. The cost-efficiency and capacity gains due to small cell deployments can be further enhanced by optimizing the number and locations of the dense small cell deployments. With network densification by 4G small cells imminent while 5G small cell upgrades envisioned, an interesting network planning dilemma emerges on whether to optimize small cell deployments for 4G or 5G small cells. In this paper, we confront this dilemma by utilizing multiobjective optimization (MO) based planning approach for comparing and contrasting performance of small cell topologies optimized for 4G and 5G deployments. Propagation computation is performed using deterministic ray-tracing dominant path model over a building and terrain map of the deployment scenario. Results show that 5G optimized scenario provides considerable network capacity gains compared to 4G optimized 5G co-location scenario for different optimal small cell topologies with same number of small cells. For instance, for 31 small cells topologies, it presents 21.5% more capacity gain relative to 4G optimized case. Furthermore, 5G optimized case presents 38% and 5% more peak and cell-edge user throughput gains, respectively.

Original languageEnglish
Title of host publicationIEEE AFRICON 2019
Subtitle of host publicationPowering Africa's Sustainable Energy for All Agenda: The Role of ICT and Engineering, AFRICON 2019
PublisherIEEE
Number of pages5
ISBN (Electronic)9781728132891
DOIs
Publication statusPublished - Sep 2019
MoE publication typeA4 Article in a conference publication
EventIEEE AFRICON Conference - Accra, Ghana
Duration: 25 Sep 201927 Sep 2019

Publication series

NameIEEE AFRICON Conference
ISSN (Print)2153-0025
ISSN (Electronic)2153-0033

Conference

ConferenceIEEE AFRICON Conference
Abbreviated titleAFRICON
CountryGhana
CityAccra
Period25/09/201927/09/2019

Keywords

  • Multiobjective optimization
  • Planning
  • Small cells
  • Ultra-dense networks

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