Talks and Poster Presentations (with Proceedings-Entry):
V. Raida, M. Lerch, P. Svoboda, M. Rupp:
"Deriving Cell Load from RSRQ Measurements";
Talk: 2018 Network Traffic Measurement and Analysis Conference (TMA),
Vienna;
06-25-2018
- 06-29-2018; in: "2018 Network Traffic Measurement and Analysis Conference (TMA)",
IEEE (ed.);
IEEE,
(2018),
6 pages.
English abstract:
The performance of wireless systems is often interference-limited. In LTE, the parameter RSRQ is connected to the system interference. A solid and sound measurement of this parameter allows for an estimation of the current level of cell load as well as interference in the current cell, enabling us to use crowdsourced performance data for network benchmarking. However, RSRQ is not straightforward to interpret.
We point out that RSRQ can be used to estimate the cell load caused by other users if it is measured at zero downlink throughput of the measuring device. In such a case we expect a~positive correlation between RSRQ and achievable throughput which we confirm by measurements in a live LTE network. Conversely, we show that if the measuring device is downloading data, a wide range of different RSRQ values can be generated. As an extreme case we present measurements with strong negative correlation between RSRQ and throughput.
The source codes of the network monitoring applications are often proprietary, we thus do not know if RSRQ samples are a) collected at zero downlink throughputs, b) during a downlink throughput test or c) a combination of both. In case a) RSRQ provides us precious additional knowledge about the cell load. In cases b) and c) it is merely useless if we cannot filter out the samples corresponding to nonzero downlink throughput.
German abstract:
The performance of wireless systems is often interference-limited. In LTE, the parameter RSRQ is connected to the system interference. A solid and sound measurement of this parameter allows for an estimation of the current level of cell load as well as interference in the current cell, enabling us to use crowdsourced performance data for network benchmarking. However, RSRQ is not straightforward to interpret.
We point out that RSRQ can be used to estimate the cell load caused by other users if it is measured at zero downlink throughput of the measuring device. In such a case we expect a~positive correlation between RSRQ and achievable throughput which we confirm by measurements in a live LTE network. Conversely, we show that if the measuring device is downloading data, a wide range of different RSRQ values can be generated. As an extreme case we present measurements with strong negative correlation between RSRQ and throughput.
The source codes of the network monitoring applications are often proprietary, we thus do not know if RSRQ samples are a) collected at zero downlink throughputs, b) during a downlink throughput test or c) a combination of both. In case a) RSRQ provides us precious additional knowledge about the cell load. In cases b) and c) it is merely useless if we cannot filter out the samples corresponding to nonzero downlink throughput.
Keywords:
LTE,downlink,cell load,throughput,reference signal received power,received signal strength indicator,reference signal received quality,crowdsourced measurements
Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_271503.pdf
Created from the Publication Database of the Vienna University of Technology.