13,177 research outputs found
Self-concatenated code design and its application in power-efficient cooperative communications
In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions
Iterative Slepian-Wolf Decoding and FEC Decoding for Compress-and-Forward Systems
While many studies have concentrated on providing theoretical analysis for the relay assisted compress-and-forward systems little effort has yet been made to the construction and evaluation of a practical system. In this paper a practical CF system incorporating an error-resilient multilevel Slepian-Wolf decoder is introduced and a novel iterative processing structure which allows information exchanging between the Slepian-Wolf decoder and the forward error correction decoder of the main source message is proposed. In addition, a new quantization scheme is incorporated as well to avoid the complexity of the reconstruction of the relay signal at the final decoder of the destination. The results demonstrate that the iterative structure not only reduces the decoding loss of the Slepian-Wolf decoder, it also improves the decoding performance of the main message from the source
Mitigation of H.264 and H.265 Video Compression for Reliable PRNU Estimation
The photo-response non-uniformity (PRNU) is a distinctive image sensor
characteristic, and an imaging device inadvertently introduces its sensor's
PRNU into all media it captures. Therefore, the PRNU can be regarded as a
camera fingerprint and used for source attribution. The imaging pipeline in a
camera, however, involves various processing steps that are detrimental to PRNU
estimation. In the context of photographic images, these challenges are
successfully addressed and the method for estimating a sensor's PRNU pattern is
well established. However, various additional challenges related to generation
of videos remain largely untackled. With this perspective, this work introduces
methods to mitigate disruptive effects of widely deployed H.264 and H.265 video
compression standards on PRNU estimation. Our approach involves an intervention
in the decoding process to eliminate a filtering procedure applied at the
decoder to reduce blockiness. It also utilizes decoding parameters to develop a
weighting scheme and adjust the contribution of video frames at the macroblock
level to PRNU estimation process. Results obtained on videos captured by 28
cameras show that our approach increases the PRNU matching metric up to more
than five times over the conventional estimation method tailored for photos
Turbo-Detected Unequal Protection MPEG-4 Wireless Video Telephony using Multi-Level Coding, Trellis Coded Modulation and Space-Time Trellis Coding
Most multimedia source signals are capable of tolerating lossy, rather than lossless delivery to the human eye, ear and other human sensors. The corresponding lossy and preferably low-delay multimedia source codecs however exhibit unequal error sensitivity, which is not the case for Shannon’s ideal entropy codec. This paper proposes a jointly optimised turbo transceiver design capable of providing unequal error protection for MPEG-4 coding aided wireless video telephony. The transceiver investigated consists of space-time trellis coding (STTC) invoked for the sake of mitigating the effects of fading, in addition to bandwidth efficient trellis coded modulation or bit-interleaved coded modulation, combined with a multi-level coding scheme employing either two different-rate non-systematic convolutional codes (NSCs) or two recursive systematic convolutional codes for yielding a twin-class unequal-protection. A single-class protection based benchmark scheme combining STTC and NSC is used for comparison with the unequal-protection scheme advocated. The video performance of the various schemes is evaluated when communicating over uncorrelated Rayleigh fading channels. It was found that the proposed scheme requires about 2.8 dBs lower transmit power than the benchmark scheme in the context of the MPEG-4 videophone transceiver at a similar decoding complexity
Binary Systematic Network Coding for Progressive Packet Decoding
We consider binary systematic network codes and investigate their capability
of decoding a source message either in full or in part. We carry out a
probability analysis, derive closed-form expressions for the decoding
probability and show that systematic network coding outperforms conventional
network coding. We also develop an algorithm based on Gaussian elimination that
allows progressive decoding of source packets. Simulation results show that the
proposed decoding algorithm can achieve the theoretical optimal performance.
Furthermore, we demonstrate that systematic network codes equipped with the
proposed algorithm are good candidates for progressive packet recovery owing to
their overall decoding delay characteristics.Comment: Proc. of IEEE ICC 2015 - Communication Theory Symposium, to appea
Structured Random Linear Codes (SRLC): Bridging the Gap between Block and Convolutional Codes
Several types of AL-FEC (Application-Level FEC) codes for the Packet Erasure
Channel exist. Random Linear Codes (RLC), where redundancy packets consist of
random linear combinations of source packets over a certain finite field, are a
simple yet efficient coding technique, for instance massively used for Network
Coding applications. However the price to pay is a high encoding and decoding
complexity, especially when working on , which seriously limits the
number of packets in the encoding window. On the opposite, structured block
codes have been designed for situations where the set of source packets is
known in advance, for instance with file transfer applications. Here the
encoding and decoding complexity is controlled, even for huge block sizes,
thanks to the sparse nature of the code and advanced decoding techniques that
exploit this sparseness (e.g., Structured Gaussian Elimination). But their
design also prevents their use in convolutional use-cases featuring an encoding
window that slides over a continuous set of incoming packets.
In this work we try to bridge the gap between these two code classes,
bringing some structure to RLC codes in order to enlarge the use-cases where
they can be efficiently used: in convolutional mode (as any RLC code), but also
in block mode with either tiny, medium or large block sizes. We also
demonstrate how to design compact signaling for these codes (for
encoder/decoder synchronization), which is an essential practical aspect.Comment: 7 pages, 12 figure
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