Source-controlled Channel Decoding Research Articles

Universal source controlled channel decoding with nonsystematic quick-look-in turbo codes

Utilization of redundancy left in a channel coded sequence can improve channel decoding performance. Stronger improvement can usually be achieved with nonsystematic encoding. However, nonsystematic codes recently proposed for this problem are not robust to the statistical parameters governing a sequence and thus should not be used without prior knowledge of these parameters. In this work, decoders of nonsystematic quick-look-in turbo codes are adapted to extract and exploit redundancy left in coded data to improve channel decoding performance. Methods, based on universal compression and denoising, for extracting the governing statistical parameters for various source models are integrated into the channel decoder by also taking advantage of the code structure. Simulation results demonstrate significant performance gains over standard systematic codes that can be achieved with the new methods for a wide range of statistical models and governing parameters. In many cases, performance almost as good as that with perfect knowledge of the governing parameters is achievable.

MAP Source-Controlled Channel Decoding with Interleavers for MPEG-4 Image Indoor Wireless Transmission Systems

In the modern day, MPEG-4 image compression technique have been commonly applied in various indoor wireless communication systems. The efficient system design mostly relies on the joint source channel coding algorithms, which aim to reduce the complexity of channel coding process, while maintaining the quality of the receiving images. In this paper, we design the MAP source-controlled channel decoders with both random and semirandom interleavers for Rician slow flat block-fading channels. The MAP-Viterbi decoder employs the residual redundancy from zerotree symbol sequences of MPEG-4 HFS packets. The interleaving processes are done after the overall channel coding process to combat the block-fading effects. The computer simulations summarize the system performance in terms of average WER and PSNR (dB). With the interleavers, the significant improvement in PSNR of about 15-17dB is obtained for both ML and MAP decoding. Also in many cases, we obtain more improvement of about 0.2-0.4dB for using MAP decoding with the interleavers.

Joint Source-Channel Decoding of Variable-Length Codes with Soft Information: A Survey

Multimedia transmission over time-varying wireless channels presents a number of challenges beyond existing capabilities conceived so far for third-generation networks. Efficient quality-of-service (QoS) provisioning for multimedia on these channels may in particular require a loosening and a rethinking of the layer separation principle. In that context, joint source-channel decoding (JSCD) strategies have gained attention as viable alternatives to separate decoding of source and channel codes. A statistical framework based on hidden Markov models (HMMs) capturing dependencies between the source and channel coding components sets the foundation for optimal design of techniques of joint decoding of source and channel codes. The problem has been largely addressed in the research community, by considering both fixed-length codes (FLC) and variable-length source codes (VLC) widely used in compression standards. Joint source-channel decoding of VLC raises specific difficulties due to the fact that the segmentation of the received bitstream into source symbols is random. This paper makes a survey of recent theoretical and practical advances in the area of JSCD with soft information of VLC-encoded sources. It first describes the main paths followed for designing efficient estimators for VLC-encoded sources, the key component of the JSCD iterative structure. It then presents the main issues involved in the application of the turbo principle to JSCD of VLC-encoded sources as well as the main approaches to source-controlled channel decoding. This survey terminates by performance illustrations with real image and video decoding systems.

Universal lossless source controlled channel decoding for I.I.D. sequences

Messages coded and transmitted over a channel usually contain some redundancy which is not utilized by channel decoding techniques, especially if its governing statistical parameters are unknown. We propose to integrate universal lossless source coding techniques into channel decoding of redundant sequences with unknown statistics to improve performance of Viterbi and turbo decoding. Simulation results demonstrate that we achieve identical bit error rate (BER) performance to nonuniversal techniques that utilize prior knowledge of the message statistics and that if redundancy exists even in an a-priori unknown form, we can improve the code performance over standard techniques.

Source-Optimized Channel Coding for Digital Transmission Channels

We present a new class of nonlinear block codes called source-optimized channel codes (SOCCs), which are particularly designed for parametric source encoding of speech, audio, and video. In contrast to conventional channel codes, the new codes are not optimized for minimizing residual bit-error rate, but maximizing the signal-to-noise ratio of transmitted source codec parameters. The decoding of SOCCs is not based on bit-error correction, but on parameter estimation. We compare SOCCs with other approaches to joint source/channel coding such as channel-optimized vector quantization, channel-constrained vector quantization, unequal error protection, and source-controlled channel decoding. In terms of performance, SOCCs show better robustness if under channel mismatch conditions. For real-world applications, SOCCs are attractive, since the separation of source and channel codec is preserved.

Hybrid symbol- and bit-based source-controlled channel decoding for MELP speech parameters

A joint source channel coding (JSCC) scheme which exploits bit-level correlation as well as symbol-level correlation efficiently in a source-controlled channel decoding (SCCD) process is proposed and applied to the mixed-excitation linear prediction (MELP) parameters of speech. A modified BCJR algorithm is also proposed for use in the SCCD algorithm. Simulation results show that our proposed scheme performs better than other redundancy-based JSCC schemes such as bit-based SCCD, soft-bit speech decoding (SBSD) and iterative source-channel decoding.

MPEG-4 image transmission using MAP source-controlled channel decoding

In this paper, we develop an error resilient variant of the MPEG-4 embedded zerotree wavelet coder, suitable for mobile fading channels. The residual redundancy in the compressed bit stream provides implicit error protection through the use of source-controlled channel decoding; no explicit channel coding is used. We propose two slight modifications to the MPEG-4 coder. The first removes the arithmetic coding in the lowest frequency subband so that hidden Markov model-based MAP estimation of both the source index and the channel state can be easily applied. The change in bit rate is negligible, while performance during severe channel fading conditions can be greatly increased. The second modification adds variable length packetization to the compressed bit stream created from the higher frequency subbands. The individual packets are independently decodable. An optional rearrangement of the bits in each packet allows MAP estimation to be applied to these subbands as well. Simulation results show a significant performance improvement for the overall system.

Channel coding and transmission aspects for wireless multimedia

Multimedia transmission has to handle a variety of compressed and uncompressed source signals such as data, text, image, audio, and video. On wireless channels the error rates are high and joint source/channel coding and decoding methods are advantageous. Also, the system architecture has to adapt to the bad channel conditions. Several examples of a joint design are given. We especially advocate the use of rate-compatible punctured systematic recursive convolutional (RCPRSC) codes which are show to lead to a straightforward and versatile unequal error protection (UEP) design. In addition, the high-end receiver could use soft outputs and source-controlled channel decoding for even better performance.

Tailbiting MAP decoders

We extend the MAP decoding algorithm of Bahl et al. (1974) to the case of tail-biting trellis codes. An algorithm is given that is based on finding an eigenvector, and another that avoids this. Several examples are given. The algorithm has application to turbo decoding and source-controlled channel decoding.

Source-controlled channel decoding

Source and channel coding have been treated separately in most cases. It can be observed that most source coding algorithms for voice, audio and images still have correlation in certain bits. Transmission errors in these bits usually account for the significant errors in the reconstructed source signal. This paper proposes a modification of the Viterbi decoding algorithm (VA) for binary trellises which uses a priori or a posteriori information about the source bit probability for better decoding in addition to soft inputs and channel state information. Analytical upper bounds for the BER of convolutional codes for this modified VA (APRI-VA) are given. The algorithm is combined with the soft output viterbi algorithm (SOVA) and an estimator for the residual correlation of the source bits to achieve source-controlled channel decoding for framed source bits. The description is simplified by an algebra for the log-likelihood ratio L(u)=log(P(u=+1)/P(u=-1)) which allows a clear definition of the "soft" values of source-, channel-, and decoded bits as well as a simplified description of the traceback version of the SOVA. Applications are given for PCM transmission and the full rate GSM speech codec. For an PCM coded oversampled bandlimited Gaussian source transmitted over Gaussian and Rayleigh channels with convolutional codes the decoding errors are reduced by a factor of 4 to 5 when the APRI-SOVA is used instead of the VA. A simple dynamic Markov correlation estimator is used. With these receiver-only modifications the channel SNR in a bad mobile environment can be lowered by 2 to 4 dB resulting in the same voice quality. Further applications are briefly discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>