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

TL;DR

This study investigates the behavior of dynamic multipath clusters at 60 GHz in an indoor environment, using a combined clustering and tracking approach to improve channel modeling accuracy for mmWave communications.

Contribution

It introduces a joint clustering-tracking framework for parameterizing the COST 2100 channel model with mmWave data, enhancing spatial consistency in channel simulations.

Findings

Clusters are effectively identified and tracked using the proposed framework.

Cluster movement, lifetime, and quantity vary with environment dynamics.

Multipath components are successfully grouped into clusters at 60 GHz.

Abstract

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.