Analyzing group behavior patterns in a cellular mobile network for 5G use‐cases

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Abstract

Summary The massive demand for broadband mobile network services are quite successfully covered already by 3G and 4G cellular mobile systems. The challenges for 5G are more diverse: answering the demands of Ultra‐Reliable Low Latency Communications (URLLC) and massive Machine Type Communications (mMTC) users—besides elevating mobile broadband to the next level. While generic, high‐level targets for KPIs (Key Performance Indicators) are widely communicated, it is not yet well‐understood how the various demands can affect the traffic mixture. Both the radio‐ and the core‐domains of the cellular network have to cope with traffic peaks, and have to obey various QoS (Quality of Service) guarantees. In order to cover these gaps, traffic‐related characteristics (data volume, signaling message types, and traffic peaks) should be determined, and this knowledge should be used during network planning, optimization, and service shaping. This paper aims to provide insights into user behavioral patterns for these three key application areas: enhanced Mobile Broadband (eMBB), URLLC and mMTC. Since traffic volume‐ and burst‐related user behavior is not expected to change suddenly, current targeted data collection on legacy mobile network links would provide a good basic insight for future, 5G usage—at least as traffic patterns. We have collected live pre‐5G mobile network data then analyzed them throughout this paper in order to reveal traffic patterns—and their distinguishing features—for the three key 5G application areas.

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