FALCON: An Accurate Real-Time Monitor for Client-Based Mobile Network Data Analytics

Abstract

Network data analysis is the fundamental basis for the development of methods to increase service quality in mobile networks. This requires accurate data of the current load in the network. The control channel analysis is a way to monitor the resource allocations and the throughput of all active subscribers in a public mobile radio cell. Previous open-source approaches require either ideal radio conditions or long-term observations in order to obtain reliable data. Otherwise, the revealed information is polluted by spurious assignments with random content. In this paper, we present a new open-source instrument for Fast Analysis of LTE Control channels (FALCON), which combines a novel shortcut-decoding approach with the most reliable techniques known to us to reduce the aforementioned requirements significantly. Long-term field measurements reveal that FALCON reduces errors in average by three orders of magnitude compared to currently the best approach. FALCON allows observations at locations with interference and enables mobile applications with single short-term tracking of the local load situation. It is compatible with numerous software defined radios and can be used on standard computers for a reliable real-time analysis.

Cellular Network Radio Monitoring and Management through Virtual UE Probes: A Study Case Based on Crowded Events

“…Since the management systems of 5G and next-generation mobile networks are likely to be user-centric [ 30 ], it will be necessary to include mechanisms capable of capturing and processing data from the user plane complementing network side log collection. Additionally, given the future network layers, split architectures will make this analysis more necessary [ 31 ].…”

Traffic-Driven Sounding Reference Signal Resource Allocation in (Beyond) 5G Networks

“…For our study, we collect a dataset of LTE traffic allocations from multiple BSs located in different areas of Madrid, Spain. For completeness, we run both the SDR-based LTE sniffer tools FALCON [11] and OWL [12] on a Linux laptop connected to a USRP B210 to decode the unencrypted information of the TTI-level traffic allocation that LTE BSs send to the UEs over the PDCCH channel. Specifically, we gather the temporary user ID (C-RNTI), the ID of the frame containing the traffic allocation for the C-RNTI, and the associated transport block size (TBS).…”

“…We evaluate the performance of TRADER by using real- Specifically, we use passive measurement tools based on software-defined radios (SDRs), FALCON [11] and OWL [12], to decode the unencrypted information of the Physical Downlink Control CHannel (PDCCH) of LTE in a fully privacypreserving manner. Our results show that TRADER largely outperforms a round robin schedule of aperiodic SRS, as it is capable of triggering more often an SRS right before the user generates traffic.…”

Towards Cooperative Data Rate Prediction for Future Mobile and Vehicular 6G Networks

“…Therefore, real time cell monitoring requires advanced methods for discovery of missed RNTI assignments and reliable DCI validation techniques. To the best of our knowledge, FALCON [10] is currently the most accurate open source instrument for performing this task which reliably discloses currently active RNTIs and reveals all DCI from PDCCH. In order to not miss DCIs that are addressed to cell-center users and include less redundancy for error correction, the FALCON sniffer must be placed in proximity of the antenna of the monitored cell.…”

“…1. We mimic such a system by combining mobile UE measurements with information about the cell-wide radio resource allocations which are revealed by analysis of Physical Downlink Control Channel (PDCCH) using the SDR-based Fast Analysis of LTE Control channels (FALCON) [10] sniffer.…”