A Study of Dynamic Multipath Clusters at 60 GHz in a Large Indoor Environment

TY - GEN

T1 - A Study of Dynamic Multipath Clusters at 60 GHz in a Large Indoor Environment

AU - Bashar, Manijeh

AU - Haneda, Katsuyuki

AU - Burr, Alister G.

AU - Cumanan, Kanapathippillai

N1 - Funding Information: The work of A. G. Burr and K. Cumanan was supported by H2020-MSCA-RISE-2015 under grant number 690750. The work on which this paper is based was carried out in collaboration with COST Action CA15104 (IRACON). Publisher Copyright: © 2018 IEEE.

PY - 2018/7/2

Y1 - 2018/7/2

N2 - The available geometry-based stochastic channel models (GSCMs) at millimetre-wave (mmWave) frequencies do not necessarily retain spatial consistency for simulated channels, which is essential for small cells with ultra-dense users. In this paper, we work on cluster parameterization for the COST 2100 channel model using mobile channel simulations at 61 GHz in Helsinki Airport. The paper considers a ray-tracer which has been optimized to match measurements, to obtain double-directional channels at mmWave frequencies. A joint clustering-tracking framework is used to determine cluster parameters for the COST 2100 channel model. The KPowerMeans algorithm and the Kalman filter are exploited to identify the cluster positions and to predict and track cluster positions respectively. The results confirm that the joint clustering-and-tracking is a suitable tool for cluster identification and tracking for our ray-tracer results. The movement of cluster centroids, cluster lifetime and number of clusters per snapshot are investigated for this set of ray-tracer results. Simulation results show that the multipath components (MPCs) are grouped into clusters at mmWave frequencies.

AB - The available geometry-based stochastic channel models (GSCMs) at millimetre-wave (mmWave) frequencies do not necessarily retain spatial consistency for simulated channels, which is essential for small cells with ultra-dense users. In this paper, we work on cluster parameterization for the COST 2100 channel model using mobile channel simulations at 61 GHz in Helsinki Airport. The paper considers a ray-tracer which has been optimized to match measurements, to obtain double-directional channels at mmWave frequencies. A joint clustering-tracking framework is used to determine cluster parameters for the COST 2100 channel model. The KPowerMeans algorithm and the Kalman filter are exploited to identify the cluster positions and to predict and track cluster positions respectively. The results confirm that the joint clustering-and-tracking is a suitable tool for cluster identification and tracking for our ray-tracer results. The movement of cluster centroids, cluster lifetime and number of clusters per snapshot are investigated for this set of ray-tracer results. Simulation results show that the multipath components (MPCs) are grouped into clusters at mmWave frequencies.

KW - Cluster identification

KW - Kalman filter

KW - KPowerMeans

KW - millimetre wave

KW - multi path components

UR - http://www.scopus.com/inward/record.url?scp=85063506018&partnerID=8YFLogxK

U2 - 10.1109/GLOCOMW.2018.8644100

DO - 10.1109/GLOCOMW.2018.8644100

M3 - Conference contribution

AN - SCOPUS:85063506018

T3 - 2018 IEEE Globecom Workshops, GC Wkshps 2018 - Proceedings

BT - 2018 IEEE Globecom Workshops, GC Wkshps 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE Globecom Workshops, GC Wkshps 2018

Y2 - 9 December 2018 through 13 December 2018

ER -