Understanding the present and future of cellular networks through crowdsourced traces

Abstract

Abstract-We focus on today's LTE systems and use realworld, crowdsourced traces to understand (i) how present-day LTE networks are deployed and to which extent they are suited to the current traffic load; (ii) how well they will withstand the traffic demand forecasted within 2020; (iii) which techniques to improve them should be pursued and how aggressively. To this end, we use two datasets, coming from WeFi and OpenSignal and available under commercial terms. We find that today's networks are composed of tangled, medium to large-sized cells, characterized by fairly high interference. Also, current networks are typically overprovisioned, but the future traffic load will pose a significant strain on them. To accommodate the forecasted mobile traffic, our study highlights the efficacy of: (i) traffic offloading for pedestrian and stationary users, (ii) increasing the available bandwidth through, e.g., spectrum refarming, (iii) mitigating interference and improving link quality for edge users through coordinated downlink transmissions. By putting in place these actions, only a negligible amount of additional cellular infrastructure will be required. Our results come from the combination of real-world traces, experimental measurements, and ITU-recommended propagation models. Each step we take is backed by real-world facts and data.

Not in My Neighborhood: A User Equipment Perspective of Cellular Planning Under Restrictive EMF Limits

“…9 is that the each BS serves almost exclusively a given portion of territory. The overlapping coverage from multiple BSs (which instead strongly affects other scenarios like in the USA [20], [21]) appears to be not so widespread in our cases.…”

“…Malandrino et al [20] analyze the mobile data measured with WeFi and OpenSignal tools in different areas of the USA. Their focus is on the LTE technology and on the characterization of LTE networks.…”

“…However, they also point out that a substantial increase of capacity is needed to sustain the predicted traffic increase in the forthcoming years. Although the works [20], [21] are surely of interest, the considered network infrastructure is deployed in the USA. Therefore, it is subject to a different set of regulations compared to other countries, which adopt strict constraints (e.g., in terms of EMF levels) when installing new BS sites.…”

Correlation-Based Feature Mapping of Crowdsourced LTE Data

“…The usual setup of a SON research study is a singledomain simulator system where KPIs and their semantics are known. In analyzing end-user-based LTE measurements, the need for matching metrics across measurement platforms has been recognized, for example to compare the performance of network providers [82,81,86].…”

“…Moreover, Li et al [81] have mapped QoS parameters across LTE network components, such as Evolved Universal Terrestrial Radio Access Network (E-UTRAN), Backhaul transport network, and Evolved Packet Core (EPC) network. Malandrino et al [86] have merged two crowdsourced LTE measurement datasets to analyze mobile traffic traces. All of the aforementioned papers propose models where the cross-domain mapping of metrics is defined by human.…”