Abstract
The consideration of ultra-wideband (UWB) and mm-wave signals allows for a channel description decomposed into specular multipath components (SMCs) and dense/diffuse multipath. In this paper, the amplitude and phase of SMCs are studied. Gaussian Process regression (GPR) is used as a tool to analyze and predict the SMC amplitudes and phases based on a measured training data set. In this regard, the dependency of the amplitude (and phase) on the angle-of-arrival/angle-of-departure of a multipath component is analyzed, which accounts for the incident angle and incident position of the signal at a reflecting surface—and thus for the reflection characteristics of the building material—and for the antenna gain patterns. The GPR model describes the similarities between different data points. Based on its model parameters and the training data, the amplitudes of SMCs are predicted at receiver positions that have not been measured in the experiment. The method can be used to predict a UWB channel impulse response at an arbitrary position in the environment.
Highlights
Future 5G wireless communication technologies and the Internet of Things (IoT) paradigm will be characterized by supporting a variety of services with high quality requirements, addressing performance metrics such as reliability, latency, data throughput, and resource-efficient use of the infrastructure [1,2,3]
We show that the Gaussian Process (GP) is capable of modeling the angle-dependencies of the specular multipath components (SMCs) amplitudes
We review the generic principle of GP regression (GPR)
Summary
Future 5G wireless communication technologies and the Internet of Things (IoT) paradigm will be characterized by supporting a variety of services with high quality requirements, addressing performance metrics such as reliability, latency, data throughput, and resource-efficient use of the infrastructure [1,2,3]. Location-awareness is founded in the observation that many parameters of the propagation channel are directly linked with the geometry of the scenario and environment, starting from the distance-dependent path loss, spatial correlation of shadowing, to the arrival angle of individual multipath components. The availability of such geometric models allows for efficient and robust location-based routing and medium access schemes, or geometry-based beam steering, to name just a few popular examples.
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