We consider the transmission of progressive image data
over noisy channels when the coded packet size is fixed. The concatenated
cyclic redundancy check (CRC) codes and ratecompatible
punctured turbo codes are used for error control and
detection. In such an application, the distortion-based optimal channel
rate allocation for unequal error protection is complex. We first
propose a suboptimal genetic algorithm–based method that not only
largely reduces the optimization complexity but also obtains performance
approaching to the results of a brute force search. In addition,
because a large packet size is usually applied when turbo
codes are used due to the fact that the coding gain is proportional to
the packet size for a given code rate, a single remaining bit error
after channel decoding may result in CRC failure and hence the
discard of the entire packet. Therefore, we further propose a
multiple-CRC structure for certain data packets so that more correctly
decoded data could be used in source decoding. The promising
performance of the proposed scheme has been demonstrated
through simulation.
In this paper, a joint source-channel coding scheme is proposed for progressive image transmission over
channels with both random bit errors and packet loss by using rate-compatible punctured Turbo codes (RCPT)
protection only. Two technical components which are different from existing methods are presented. First, a
data frame is divided into multiple CRC blocks before being coded by a turbo code. This is to secure a high
turbo coding gain which is proportional to the data frame size. In the mean time, the beginning blocks in a
frame may still be usable although the decoding of the entire frame fails. Second, instead of employing product
codes, we only use RCPT, along with an interleaver, to protect images over channels with combined distortion
including random errors and packet loss. With this setting, the effect of packet loss is equivalent to randomly
puncturing turbo codes. As a result, the optimal allocation of channel code rates is required for the random
errors only, which largely reduces the complexity of the optimization process. The effectiveness of the proposed
schemes is demonstrated with extensive simulation results.
In this paper, we propose a joint source-channel coding scheme for progressive image transmission over binary
symmetric channels(BSCs). The algorithm of set partitioning in hierarchical trees (SPIHT) is used for source
coding. Rate-compatible punctured Turbo codes (RCPT) concatenated with multiple cyclic redundancy check
(CRC) codes are adopted for channel protection. For a fixed transmission rate, the source and channel code rates
are jointly optimized to maximize the expected image quality at the receiver. Two technical components which
are different from existing methods are presented. First, a long data packet is divided into multiple CRC blocks
before being coded by turbo codes. This is to secure a high coding gain of Turbo codes which is proportional
to the interleaver size. In the mean time, the beginning blocks in a packet may still be useable although the
decoding of the entire packet fails. Second, instead of using exhaustive search, we give a genetic algorithm (GA)
based optimization method to find the appropriate channel code rates with low complexity. The effectiveness of
the scheme is demonstrated through simulations.
KEYWORDS: Binary data, Detection and tracking algorithms, Electrical engineering, Data compression, Forward error correction, Data communications, Multimedia, Computer programming, Distortion, Signal to noise ratio
In this paper, we discuss the maximum a-posteriori probability (MAP) decoding of variable length codes(VLCs) and propose a novel decoding scheme for the Huffman VLC coded data in the presence of noise. First, we provide some simulation results of VLC MAP decoding and highlight some features that have not been discussed yet in existing work. We will show that the improvement of MAP decoding over the conventional VLC decoding comes mostly from the memory information in the source and give some observations regarding the advantage of soft VLC MAP decoding over hard VLC MAP decoding when AWGN channel is considered. Second, with the recognition that the difficulty in VLC MAP decoding is the lack of synchronization between the symbol sequence and the coded bit sequence, which makes the parsing from the latter to the former extremely complex, we propose a new MAP decoding algorithm by integrating the information of self-synchronization strings (SSSs), one important feature of the codeword structure, into the conventional MAP decoding. A consistent performance improvement
and decoding complexity reduction over the conventional VLC MAP decoding can be achieved with the new scheme.
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