MMNIMay 24, 2017

HTTP adaptive streaming with indoors-outdoors detection in mobile networks

arXiv:1705.08809v122 citations
Originality Incremental advance
AI Analysis

This addresses video streaming reliability for mobile users in buildings, but it is incremental as it builds on existing adaptive streaming methods with a new sensor-based detection component.

The paper tackled poor video streaming quality when mobile users enter buildings by developing a Bayesian detector using smartphone sensors to classify indoor/outdoor coverage and an adaptive streaming algorithm to improve playback stability. Measurements in an office building showed high detector accuracy and superior Quality-of-Experience for the algorithm.

In mobile networks, users may lose coverage when entering a building due to the high signal attenuation at windows and walls. Under such conditions, services with minimum bit-rate requirements, such as video streaming, often show poor Quality-of-Experience (QoE). We will present a Bayesian detector that combines measurements from two Smartphone sensors to decide if a user is inside a building or not. Based on this coverage classification, we will propose an HTTP adaptive streaming (HAS) algorithm to increase playback stability at a high average bitrate. Measurements in a typical office building show high accuracy for the presented detector and superior QoE for the proposed HAS algorithm.

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