Cloud Analytics for Wireless Metric Prediction - Framework and Performance

The knowledge of a future link quality for a user equipment (UE) in wireless networks may be used by the application and TCP layer so that user´s experience is optimized. The metrics that are relevant are available at the core of the radio link and the application or TCP layers have no knowledge of the wireless metrics. With a signaling protocol to the application/TCP layer and a prediction mechanism of the future link quality the applications will be able to avoid buffer overflows and/or congestion. In this paper we identify metrics that are suitable for application/TCP control, and analyze the performance of the prediction of the metrics. We show that the prediction of wireless metrics can be made with low error (3-10% MAPE) even with high cloud latency. This is a significant result as it states that predictions in the cloud of even short term LTE metrics are possible and that the predictions are fairly accurate to influence the proper operation of applications/TCP in wireless environments.