Link Error Analysis and Modeling for Video Streaming Cross-Layer Design in Mobile Communication Networks

Abstract

Particularly in wireless communications, link errors severely affect the quality of the services due to the high error probability and the specific error characteristics (burst errors) in the radio access part of the network. In this work, we show that thorough analysis and appropriate modeling of radio-link error behavior are essential to evaluate and optimize higher layer protocols and services. They are also the basis for finding network-aware crosslayer processing algorithms which are capable of exploiting the specific properties of the link error statistics, such as predictability. This document presents the analysis of the radio link errors based on measurements in live Universal Mobile Telecommunication System (UMTS) radio access networks as well as new link error models originating from that analysis. It is shown that the knowledge of the specific link error characteristics leads to significant improvements in the quality of streamed video by applying the proposed novel network-and content-aware cross-layer scheduling algorithms. Although based on live UMTS network experience, many of the conclusions in this work are of general validity and are not limited to UMTS only.

Performance of hybrid ARQ on dual-branch diversity receiver in Rayleigh fading channel

“…The smallest TTI is 10 ms which is the same as the radio frame length [16]. For example, PHY model generates a radio frame at a fixed period of 10 ms (for 384 kbps and spread factor (SF) of 8) and 20 ms (for 64 kbps with SF=32) [18]. The RLC entity receives a PDCP PDU which comprises an IP packet of 552 bytes or an ACK of 40 bytes, and additionally PDCP header of 1 byte.…”

Delay Modeling for 3G Mobile Multimedia Services QoE Estimation

“…These advanced models represent with higher fidelity the behavior of the wireless link, far beyond typical ones based on independent losses. As a conclusion of this preliminary analysis note here that in our study we will consider UMTS RLC AM mode, SR-ARQ retransmission scheme, with 12 TB/TTI configuration, not-in-order delivery and complex bursty air error model in mobility based on modifications of Gilbert-Elliot's one in [7]. These considerations are not trivial since many studies do not state them explicitly and usually yield inaccurate simulation results.…”

“…In [7] this behavior is modeled by means of modified Markov chains. For a dynamic scene (with mobility), it is concluded that the behavior of error bursts at TB level is similar to those of burst at TTI level, and this is modeled with a modified Gilbert-Elliot model (see [5] and [6]) at TTI level.…”

Cross–layer cross–domain adaptation of mobile video services

“…However, in both cases the loss model is implemented at IP level. In our case, the bursty error pattern is implemented at UMTS Radio Link Control (RLC) level following the results shown in [9], where the error pattern is obtained from live UMTS network traces. This feature entails a better emulation of the combined effects of the service-level settings and the experienced UMTS performance conditions.…”