Blockage and Ray Tracing Propagation Model in 3GPP Specified Industrial Environment

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

Abstrakti

The Fifth Generation (5G) of communication systems is expected to operate at sub-6GHz band and at Millimeter Wave (mmWave) frequencies. The 28GHz band and 60GHz band are two lucrative and potential bands for 5G, and are getting popular since they enable standalone private network for Industrial Internet of Things (IIoT). In order to implement IIoT in practice, there is a clear need to understand the propagation characteristics in Indoor Factory (InF) environments that are characterized by high density of blockers. It is of utmost importance to ensure reliable and conclusive coverage for industry automation and IIoT. In order to address this challenge, our aim is to study and compare the performance of simplistic Line of Sight (LoS) based Blockage Model (BM) and a deterministic Ray Tracing (RT) model in a specific InF environment defined by the 3rd Generation Partnership Project (3GPP). This environment includes dense clutter of blockers and ceiling mounted Base Stations (BSs) operating at 3.5GHz, 28GHz and 60GHz frequency. We also study the impact of BS densification. Performance is measured using the received power level, Signal to Interference plus Noise Ratio (SINR), outage ratio, relative throughput gain among other Key Performance Indicators (KPIs). Simulation results and related discussion provides insightful information about communication in indoor industrial environment under different circumstances.

AlkuperäiskieliEnglanti
Otsikko35th International Conference on Information Networking, ICOIN 2021
KustantajaIEEE
Sivut397-402
Sivumäärä6
ISBN (elektroninen)9781728191003
DOI - pysyväislinkit
TilaJulkaistu - 13 tammikuuta 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Information Networking - Jeju Island, Etelä-Korea
Kesto: 13 tammikuuta 202116 tammikuuta 2021
Konferenssinumero: 35

Conference

ConferenceInternational Conference on Information Networking
LyhennettäICOIN
MaaEtelä-Korea
KaupunkiJeju Island
Ajanjakso13/01/202116/01/2021

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