Electromagnetic Parameter Calibration for a Broadband Ray-Launching Simulator With SAGE Algorithm for Millimeter-Wave Communications

Abstract

The millimeter-wave (mmWave) communication is a promising solution to future high-speed data transmission. To study the impact of its wireless channel, a ray-launching simulator is developed to generate deterministic channel models according to realistic scenario descriptions. For such channel modeling, the material parameters play an important role in the electromagnetic numerical computing of multi-path components (MPCs) and should be calibrated according to channel measurement results. Our contribution in this paper is threefold: we conduct the channel measurement in an indoor scenario for extracting mmWave channel characteristics, apply the Hungarian algorithm to pair measured and simulated propagation MPCs and apply the SAGE algorithm for the parameter calibration of materials impacting on the MPCs. Note that the proposed material parameter calibration method is general for the various radio propagation environment, not limited by the indoor or outdoor scenarios. Moreover, it avoids independent measurement of specific materials in a given scenario, thus greatly reducing the difficulty of obtaining material parameters. The result shows that the space alternating generalized expectationmaximization (SAGE) algorithm achieves a good match between measurement and simulation with a reasonable computational effort. INDEX TERMS Channel measurement, Hungarian algorithm, millimeter-wave communications, raylaunching simulation, SAGE algorithm.

Terahertz Wireless Channels: A Holistic Survey on Measurement, Modeling, and Analysis

“…This has been applied and analyzed in the Hannover scenario including BSs with wireless and fiber backhaul links, taking atmospheric effects into account [211]- [213]. Besides, Peng et al have developed and used a new broadband ray-launching-based channel simulator [214]. It is based on the deterministic modeling by ray-launching as introduced in [124], and can generate deterministic channel models according to realistic scenario descriptions.…”

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