Edward Grinshpun

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 users 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.

Long-term application-level wireless link quality prediction

The knowledge of a future throughput value for a user equipment (UE) in Long Term Evolution (LTE) or any other transmission technology is very valuable. It can be used in rate adaptation algorithms so that radio channel congestions may be mitigated thus allowing for better quality of experience of the wireless user. Such control usually would happen at the application layer so that the control loops at different layers may work together and thus create a stable operating point. However, the metrics that are learned and predicted are available at the core of the radio link. In this paper we identify a suitable application-level link quality metric (which we call bitsU/prb) for prediction, and analyze the performance of the predictions at differing Rayleigh velocities. We find that the prediction of the application-level link quality can be 90 to 97 % accurate.

Low latency DASH based streaming over LTE

Dynamic Adaptive Streaming over HTTP (DASH) is becoming the de facto technique for video delivery, especially for VoD services. Although 3GPP has specified carriage of DASH over eMBMS for Live Streaming, eMBMS is not available everywhere (operators are starting service rollout) and it is only worthwhile for reasonably large number of users due to the static SFN resource allocation for those services. Thus, Live Streaming using DASH over unicast connections is still necessary, which may suffer from playback interruptions when the throughput varies since the low end-to-end latency for live streaming requires small buffers. In order to cope with network throughput variations in mobile networks, we propose the usage of scalable video coding, combining it with parallel TCP connections and prioritizing the most important data of the scalable video. We show that using LTE non-GBR bearers for prioritization playback interruptions can be avoided.

Intelligent connection manager for seamless interworking of multi-technology mobile devices

As wireless service providers ramp up their Long Term Evolution (LTE) installations, and telecommunications and cable operators continue to expand Wi-Fi coverage, 100 percent wireless coverage with overlapping areas of 3G, 4G, and Wi-Fi access is becoming a reality. Ensuring that a multi-mode device can roam across different radio access technologies while maintaining seamless session and service continuity across virtual private network (VPN), Voice over Internet Protocol (VoIP), and streaming video applications is critical. Differences in 3GPP, 3GPP2, and WiMAX standards led to the absence of uniform interworking solutions. Specific interworking standards per access technology pair define the behavior and interfaces for common core network components including the IP anchor, AAA, and HSS, as well as the IP Multimedia Subsystem (IMS). This paper discusses the Intelligent Wireless Connection Manager (IWCM), a critical component of a mobile device platform that enables seamless and transparent inter technology mobility for user applications through IP session continuity, make-before-break handoff algorithms, and uniform quality of service (QoS) and policy management APIs.