We mentioned that LT-SF codes are designed to be resilient to loss in feedback channel in contrast to all existing work [102, 113–116], and their decoding recovery rate does not considerably deteriorate for εf b ∈ [0, 1). We evaluate the effect of feedback loss
on the performance of LT-SF codes and SLT codes. Assume that the loss rate of the feedback channel is εf b = 0.9 (which is not known to encoder and decoder),
hence 90% of the feedbacks are lost in transmission. Note, that in a lossy forward channel the degree-one acknowledgements may also be dropped while f b1 or f b2 may
have already been delivered. In the case of f b2 loss, the retransmission compensates
this loss. However, in case of f b1 loss, the encoder shifts the degree distribution
accordingly while the decoder remains unaware of this shift. In this case, feedback retransmission is not even required since the degree distribution shift has already occurred. Therefore, we consider the worst case in our simulations and assume that if an acknowledgement is lost the distribution shifting does not occur as well. Figure
5.9 shows the performance of LT-SF codes and SLT codes for k = 1000 and εf b = 0.9. 1 1.1 1.2 1.3 1.4 1.5 10−8 10−6 10−4 10−2 100 γ B E R LT-SF, εf b= 0.9 LT-SF, εf b= 0 SLT, εf b= 0.9 SLT, εf b= 0
Figure 5.9 Effect of 90% feedback loss on the performance of SLT and LT-SF codes
employing VMD.
Figure 5.9 shows the excellent resilience of LT-SF codes to feedback loss in con- trast to SLT codes. In practice, the performance of SLT codes approach that of regular LT codes as the feedback loss ratio increases. To the best of our knowledge robustness against feedback loss had not been considered in any existing work and this significantly distinguishes LT-SF codes.
5.4 Conclusion
In this chapter, we proposed LT-SF codes that are LT codes with smart feedback, which alleviate the low performance of LT codes for short data-block lengths. We proposed to employ two types of feedbacks according to the status and needs of the decoder. In LT-SF codes, the decoder may inform the encoder with the total number of decoded input symbols by the first type of feedback or request a certain input symbol from the encoder employing second type of feedback. We designed three algorithms for LT-SF codes that described how to analyze the decoder’s buffer and request a suitable input symbol. In addition, employing a novel idea we made LT-SF
code resilient against high loss rates in the feedback channel. We analyzed LT-SF codes and discussed its advantages.
We showed that our contribution in the design of LT-SF codes compared to ex- isting work is fourfold. LT-SF codes reduce the coding overhead for a successful decoding and decrease the total number of feedbacks. Further, we observed that overall runtime required for a complete LT-SF decoding is lower than that of existing work. Finally and most importantly, LT-SF codes’ performance does not considerably degrade at large loss rates in the feedback channel.
CHAPTER 6
UNEQUAL ERROR PROTECTION RATELESS CODING IN VIDEO TRANSMISSION
So far, we have investigated various aspects of rateless codes and their advantages. In this Chapter, we demonstrate how UEP-rateless codes can be employed to increase video transmission efficiency compared to the case where conventional EEP-rateless codes are employed. First, we employ UEP-rateless codes to provide more protection for more important frames in a video stream, namely I- and P -frames. This increases the received video quality or equivalently decreases the amount of transmitted data to reach a certain video quality. Next, we utilize UEP-rateless codes to design a novel periodic broadcasting video-on-demand protocol with reduced startup delay. We discuss the advantages of our proposed algorithms and evaluate their performances employing numerical simulations.
6.1 UEP-Rateless Codes in MPEG Video Transmission
In this section, we propose a coding scheme that employs UEP-rateless codes to pro- vide more protection for video frames with higher influence on the quality of the displayed video. Previously, several work have addressed this problem. Authors in [121–124] propose to employ different Reed-Solomon codes [125] to separately encode each frame/layer of the video according to its importance. By assigning a larger cod- ing overhead to more important video frames/layers they have shown that a higher video quality can be achieved. However, since these algorithms have employed fixed-
rate Reed-Solomon codes, the transmitter needs to have an estimate of the channel erasure rate to set the appropriate coding rates to obtain an efficient video transmis- sion scheme. This information is not always available at transmitter. Further, due to high complexity of Reed-Solomon codes implementation of these algorithms may not be feasible in applications with constrained resources.
Authors in [126] propose to have a higher protection on GOP header and motion vectors instead of I- and P -frames employing LDPC codes [127]. Similar to Reed- Solomon codes, LDPC codes impose a fixed coding rate, which may not be of interest in some applications. Authors in [128] propose an MPEG video transmission scheme which provides more protection for I-frames only by transmitting multiple copies of I-frames instead of using UEP codes. This video transmission scheme may be suboptimal since a large amount of redundant packets are transmitted from I-frames and the higher importance of P -frames compared to B-frames is not considered.
In contrast to previous studies, our proposed algorithm employs UEP-rateless codes. Thus it does not need to have any knowledge about the channel’s erasure rate. Further, we propose to encode all frames of one GOP with a single UEP-rateless code instead of multiple EEP codes. This idea considerably reduces the coding/decoding overhead and complexity.