We consider a windowed decoding scheme for LDPC convolutional codes that is based on the belief-propagation (BP) algorithm. We discuss the advantages of this decoding scheme and identify certain characteristics of LDPC convolutional code ensembles that exhibit good performance with the windowed decoder. We will consider the performance of these ensembles and codes over erasure channels with and without memory. We show that the structure of LDPC convolutional code ensembles is suitable to obtain performance close to the theoretical limits over the memoryless erasure channel, both for the BP decoder and windowed decoding. However, the same structure imposes limitations on the performance over erasure channels with memory.

We consider terminated LDPC convolutional codes (LDPC-CC) constructed from photographs and explore the performance of these codes on correlated erasure channels including a single-burst channel (SBC) and Gilbert-Elliott channel (GEC). We consider code performance with a latency-constrained message passing decoder and the belief propagation decoder. We give theoretical bounds on the code efficiency over the SBC and describe a construction that achieves this bound.We show that the designed codes with belief propagation (BP) decoding perform as well as the regular LDPC-CCs presented in the literature on the binary erasure channel (BEC) and the GEC, while achieving significant gains on the SBC. In the case of windowed decoding, our codes perform much better than the best known regular LDPC-CCs over the BEC and the GEC, with very low decoding latencies.

Providing low-latency high-quality data services to mobile terminals has become a mandatory requirement for all mobile broadband standards. Therefore, effective countermeasures against mobile channel impairments, like small- and largescale fading, are of the utmost importance whenever traditional physical layer channel codes do not provide sufficient resilience or request too much hardware resources. Among the possible countermeasures, the paper investigates the application of packet layer coding, which basically consists in applying forward error control techniques at upper layer (UL-FEC). In the paper the UL-FEC decoder performance analytical model already developed by authors is generalized and extended to include nonperiodic shadowing and small-scale fading. Analytical results are then validated through numerical simulation considering a real application scenario.

The paper investigates coding and encapsulation techniques for the possible extension of the digital video broadcasting-return channel satellite (DVB-RCS) to ensure a global coverage for mobile terminals. specifically, link layer- forward error correction (LL-FEC) appears to be a reliable solution, allowing to improve the C/N performance and to counteract the Doppler effect typical of mobile channels, avoiding scalability and latency issues of Automatic Repeat reQuest (ARQ) approaches. In the paper we evaluate LL-FEC performance when applied to the railway environment. It is shown how this scenario deeply affects the LL-FEC code performance both in the multi protocol encapsulation (MPE), and the generic stream encapsulation (GSE) cases. In order to counteract this performance reduction two different approaches are considered. In the first case, we increase the number of rows of the LL-FEC Reed Solomon (RS) matrix. In the second case we exploit the sliding encoding mechanism. We also introduce a modified version of GSE that shows reduced overhead and improved performance. Results show that DVB-RCS can greatly benefit from LL-FEC RS coding in reducing residual errors that cannot be counteracted at the physical layer for efficiency reasons.

The growing market of Mobile TV requires automated adaptation of standard TV footage to small size displays. Especially extreme long shots (XLS) depicting distant objects can spoil the user experience, e.g. in soccer content. Automated zooming schemes can improve the visual experience if the resulting footage meets user expectations in terms of the visual detail and quality but does not omit valuable context information. Current zooming schemes are ignorant of beneficial zoom ranges for a given target size when applied to standard definition TV footage. In two experiments 84 participants were able to switch between original and zoom enhanced soccer footage at three sizes - from 320x240 (QVGA) down to 176x144 (QCIF). Eye tracking and subjective ratings showed that zoom factors between 1.14 and 1.33 were preferred for all sizes. Interviews revealed that a zoom factor of 1.6 was too high for QVGA content due to low perceived video quality, but beneficial for QCIF size. The optimal zoom depended on the target display size. We include a function to compute the optimal zoom for XLS depending on the target device size. It can be applied in automatic content adaptation schemes and should stimulate further research on the requirements of different shot types in video coding.