Progressive transmission of images over memoryless noisy channels

An embedded source code allows the decoder to reconstruct the source progressively from the prefixes of a single bit stream. It is desirable to design joint source-channel coding schemes which retain the capability of progressive reconstruction in the presence of channel noise or packet loss. Here, we address the problem of joint source-channel coding of images for progressive transmission over memoryless bit error or packet erasure channels. We develop a framework for encoding based on embedded source codes and embedded error correcting and error detecting channel codes. For a target transmission rate, we provide solutions and an algorithm for the design of optimal unequal error/erasure protection. Three performance measures are considered: the average distortion, the average peak signal-to-noise ratio, and the average useful source coding rate. Under the assumption of rate compatibility of the underlying channel codes, we provide necessary conditions for progressive transmission of joint source-channel codes. We also show that the unequal error/erasure protection policies that maximize the average useful source coding rate allow progressive transmission with optimal unequal protection at a number of intermediate rates     

Optimal resource allocation for wireless video over CDMA networks

We present a multiple-channel video transmission scheme in wireless CDMA networks over multipath fading channels. We map an embedded video bitstream, which is encoded into multiple independently decodable layers by 3D-ESCOT video coding technique, to multiple CDMA channels. One video source layer is transmitted over one CDMA channel. Each video source layer is protected by a product channel code structure. A product channel code is obtained by the combination of a row code based on rate compatible punctured convolutional code (RCPC) with cyclic redundancy check (CRC) error detection and a source-channel column code, i.e., systematic rate-compatible Reed-Solomon (RS) style erasure code. For a given budget on the available bandwidth and total transmit power, the transmitter determines the optimal power allocations and the optimal transmission rates among multiple CDMA channels, as well as the optimal product channel code rate allocation, i.e., the optimal unequal Reed-Solomon code source/parity rate allocations and the optimal RCPC rate protection for each channel. In formulating such an optimization problem, we make use of results on the large-system CDMA performance for various multiuser receivers in multipath fading channels. The channel is modeled as the concatenation of wireless BER channel and a wireline packet erasure channel with a fixed packet loss probability. By solving the optimization problem, we obtain the optimal power level allocation and the optimal transmission rate allocation over multiple CDMA channels. For each CDMA channel, we also employ a fast joint source-channel coding algorithm to obtain the optimal product channel code structure. Simulation results show that the proposed framework allows the video quality to degrade gracefully as the fading worsens or the bandwidth decreases, and it offers improved video quality at the receiver.     

Transport of wireless video using separate, concatenated, and jointsource-channel coding

The transmission of video over time-varying wireless communication channels can benefit from the use of joint source-channel (JSC) coding methods. We survey relevant research in JSC code design and discuss how this work can be used for video compression and transmission. A main focus is the use of estimation-based techniques to take advantage of the residual redundancy present at the output of the source encoder. As noted in previous work, the combination of the source encoder and channel can often be modeled as a hidden Markov model. This statistical framework is the basis for state estimation and minimum mean-square error estimation procedures for JSC decoding, and it can also be used to develop channel state and channel parameter estimation methods. We discuss these approaches, along with work that also incorporates modulation, channel coding, and rate allocation within the JSC design. The integration of these methods into video compression standards is considered     

Coding and Common Reconstruction

This work studies problems of source and joint source-channel coding under the requirement that the encoder can produce an exact copy of the compressed source constructed by the decoder. This requirement, termed here as the common reconstruction constraint (CR), is satisfied automatically in rate-distortion theory for single sources. However, in the common formulation of problems of lossy source coding with side information at the decoder (the Wyner-Ziv problem), distributed source coding, and joint source-channel coding for networks, the destination can exploit the information it receives in a manner that cannot be exactly reproduced at the sender side. Some applications, like the transmission of sensitive medical information, may require that both sides-the sender and the receiver-will share a common version of the compressed data, for the purpose of future discussions or consulting. The purpose of this work is to study the implications of CR constraints on the achievable rates in scenarios of lossy source coding and lossy transmission of sources. Three problems are examined: source coding with side information at the decoder, simultaneous transmission of data and state over state-dependent channels, and joint source-channel coding for the degraded broadcast channel. Single-letter characterizations of the optimal performance are developed for these problems, under corresponding CR constraints. Implications of this constraint on problems of joint source-channel coding in networks are discussed.     

Distributed Video Coding

Distributed coding is a new paradigm for video compression, based on Slepian and Wolf's and Wyner and Ziv's information-theoretic results from the 1970s. This paper reviews the recent development of practical distributed video coding schemes. Wyner-Ziv coding, i.e., lossy compression with receiver side information, enables low-complexity video encoding where the bulk of the computation is shifted to the decoder. Since the interframe dependence of the video sequence is exploited only at the decoder, an intraframe encoder can be combined with an interframe decoder. The rate-distortion performance is superior to conventional intraframe coding, but there is still a gap relative to conventional motion-compensated interframe coding. Wyner-Ziv coding is naturally robust against transmission errors and can be used for joint source-channel coding. A Wyner-Ziv MPEG encoder that protects the video waveform rather than the compressed bit stream achieves graceful degradation under deteriorating channel conditions without a layered signal representation.     

Joint source-channel coding for wireless object-based video communications utilizing data hiding.

In recent years, joint source-channel coding for multimedia communications has gained increased popularity. However, very limited work has been conducted to address the problem of joint source-channel coding for object-based video. In this paper, we propose a data hiding scheme that improves the error resilience of object-based video by adaptively embedding the shape and motion information into the texture data. Within a rate-distortion theoretical framework, the source coding, channel coding, data embedding, and decoder error concealment are jointly optimized based on knowledge of the transmission channel conditions. Our goal is to achieve the best video quality as expressed by the minimum total expected distortion. The optimization problem is solved using Lagrangian relaxation and dynamic programming. The performance of the proposed scheme is tested using simulations of a Rayleigh-fading wireless channel, and the algorithm is implemented based on the MPEG-4 verification model. Experimental results indicate that the proposed hybrid source-channel coding scheme significantly outperforms methods without data hiding or unequal error protection.     

Near-Shannon/Slepian-Wolf performance for unknown correlated sources over AWGN channels

We consider the problem of joint source-channel coding of two correlated binary information sequences. Instead of compressing the information using source coding, both sequences are independently channel encoded and transmitted over two independent additive white Gaussian noise channels. No information about the correlation between the sources is required in the encoding process. The correlation between both sequences is exploited at the receiver, allowing reliable communications at signal-to-noise ratios very close to the theoretical limits established by the combination of Shannon and Slepian-Wolf theorems. This occurs even when the correlation between sources is not known at the decoder, since it can be estimated jointly with the iterative decoding process.     

LDPC code design for asynchronous Slepian-Wolf coding

We consider asynchronous Slepian-Wolf coding where the two encoders may not have completely accurate timing information to synchronize their individual block code boundaries, and propose LDPC code design in this scenario. A new information-theoretic coding scheme based on source splitting is provided, which can achieve the entire asynchronous Slepian-Wolf rate region. Unlike existing methods based on source splitting, the proposed scheme does not require common randomness at the encoder and the decoder, or the construction of super-letter from several individual symbols. We then design LDPC codes based on this new scheme, by applying the recently discovered source-channel code correspondence. Experimental results validate the effectiveness of the proposed method.     

Joint source-channel coding for motion-compensated DCT-based SNR scalable video

In this paper, we develop an approach toward joint source-channel coding for motion-compensated DCT-based scalable video coding and transmission. A framework for the optimal selection of the source and channel coding rates over all scalable layers is presented such that the overall distortion is minimized. The algorithm utilizes universal rate distortion characteristics which are obtained experimentally and show the sensitivity of the source encoder and decoder to channel errors. The proposed algorithm allocates the available bit rate between scalable layers and, within each layer, between source and channel coding. We present the results of this rate allocation algorithm for video transmission over a wireless channel using the H.263 Version 2 signal-to-noise ratio (SNR) scalable codec for source coding and rate-compatible punctured convolutional (RCPC) codes for channel coding. We discuss the performance of the algorithm with respect to the channel conditions, coding methodologies, layer rates, and number of layers.     

Layered Wyner–Ziv Video Coding

Following recent theoretical works on successive Wyner-Ziv coding (WZC), we propose a practical layered Wyner-Ziv video coder using the DCT, nested scalar quantization, and irregular LDPC code based Slepian-Wolf coding (or lossless source coding with side information at the decoder). Our main novelty is to use the base layer of a standard scalable video coder (e.g., MPEG-4/H.26L FGS or H.263+) as the decoder side information and perform layered WZC for quality enhancement. Similar to FGS coding, there is no performance difference between layered and monolithic WZC when the enhancement bitstream is generated in our proposed coder. Using an H.26L coded version as the base layer, experiments indicate that WZC gives slightly worse performance than FGS coding when the channel (for both the base and enhancement layers) is noiseless. However, when the channel is noisy, extensive simulations of video transmission over wireless networks conforming to the CDMA2000 1X standard show that H.26L base layer coding plus Wyner-Ziv enhancement layer coding are more robust against channel errors than H.26L FGS coding. These results demonstrate that layered Wyner-Ziv video coding is a promising new technique for video streaming over wireless networks     

基于分离信源信道码的相关信源在有噪广播信道下的可靠和安全传输

从信息论的角度对相关信源在离散无记忆广播信道下可靠和安全传输的问题进行研究。2个信源经过有噪信道分别到达各自指定的目的节点并被无损恢复,同时还要保证信源信息对于非指定的目的节点要有一定的保密性。采用信源信道分离的随机码策略,得到相关信源在一般广播信道下能够可靠和安全传输的充分条件。当2个信源的公共信息为二者的互信息时,可获得最佳压缩传输效率,并且能够做到信源信息传输的部分绝对保密。当广播信道采用退化信源集或满足more capable广播信道性质时,得到了可靠和安全传输的充分必要条件,此时分离信源信道码为最优码。     

Layered Wyner-Ziv video coding.

Following recent theoretical works on successive Wyner-Ziv coding (WZC), we propose a practical layered Wyner-Ziv video coder using the DCT, nested scalar quantization, and irregular LDPC code based Slepian-Wolf coding (or lossless source coding with side information at the decoder). Our main novelty is to use the base layer of a standard scalable video coder (e.g., MPEG-4/H.26L FGS or H.263+) as the decoder side information and perform layered WZC for quality enhancement. Similar to FGS coding, there is no performance difference between layered and monolithic WZC when the enhancement bitstream is generated in our proposed coder. Using an H.26L coded version as the base layer, experiments indicate that WZC gives slightly worse performance than FGS coding when the channel (for both the base and enhancement layers) is noiseless. However, when the channel is noisy, extensive simulations of video transmission over wireless networks conforming to the CDMA2000 1X standard show that H.26L base layer coding plus Wyner-Ziv enhancement layer coding are more robust against channel errors than H.26L FGS coding. These results demonstrate that layered Wyner-Ziv video coding is a promising new technique for video streaming over wireless networks.     

Packet-by-Packet Adaptive Scheme for Video Coding and Transmission Over Wireless IP Networks Using Rate-Compatible Punctured Turbo (RCPT) Codes

In this paper, we consider real-time video coding and transmission over packet-switched wireless IP networks, such as WLAN, using RCPT codes and joint source-channel coding (JSCC) with concentration on a packet-by-packet adaptive scheme. We present a systematic design methodology to enable the applicability of JSCC techniques. The performance of H.263+ video coding and transmission over wireless channel modeled as slow Rician fading channels using this approach is studied. Results indicate that a packet-by-packet adaptive RCPT-JSCC approach is of significant advantage for real-time video applications and leads to more acceptable video delivery quality over interference-limited and time-varying wireless networks.     

A low-complexity rate allocation algorithm for joint source-channel video coding

The problem of enabling robust video transmission over lossy networks has become increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks. The more the coding process relies on an intensive use of prediction to improve the coding gain, the more the reconstructed sequence proves to be sensitive to information losses. As a matter of fact, it is necessary to introduce some redundant data in order to increase the robustness of the coded bit stream. A possible solution can be found filling a matrix structure with RTP packets and applying a Forward Error Correction (FEC) code on its rows. However, the matrix size and the chosen FEC code affect the performance of the coding system. The paper proposes a novel adaptation technique that tunes the amount of redundant information included in the packet stream and differs from previously proposed solutions since it relies on the percentage of null quantized transform coefficients in place of the activity or the Mean Square Error (MSE). This strategy is then integrated in a joint source-channel coder rate allocation algorithm that shares the available bits between the H.264/AVC coder and the channel coder according to the significance of the frame in the decoding process. Experimental results show that the presented approach significantly improves the quality of the reconstructed sequences at the decoder with respect to activity-based strategies and requires a low computational complexity.     

Transmission of nonuniform memoryless sources via nonsystematic turbo codes

We investigate the joint source-channel coding problem of transmitting nonuniform memoryless sources over binary phase-shift keying-modulated additive white Gaussian noise and Rayleigh fading channels via turbo codes. In contrast to previous work, recursive nonsystematic convolutional encoders are proposed as the constituent encoders for heavily biased sources. We prove that under certain conditions, and when the length of the input source sequence tends to infinity, the encoder state distribution and the marginal output distribution of each constituent recursive convolutional encoder become asymptotically uniform, regardless of the degree of source nonuniformity. We also give a conjecture (which is empirically validated) on the condition for the higher order distribution of the encoder output to be asymptotically uniform, irrespective of the source distribution. Consequently, these conditions serve as design criteria for the choice of good encoder structures. As a result, the outputs of our selected nonsystematic turbo codes are suitably matched to the channel input, since a uniformly distributed input maximizes the channel mutual information, and hence, achieves capacity. Simulation results show substantial gains by the nonsystematic codes over previously designed systematic turbo codes; furthermore, their performance is within 0.74-1.17 dB from the Shannon limit. Finally, we compare our joint source-channel coding system with two tandem schemes which employ a fourth-order Huffman code (performing near-optimal data compression) and a turbo code that either gives excellent waterfall bit-error rate (BER) performance or good error-floor performance. At the same overall transmission rate, our system offers robust and superior performance at low BERs (< 10/sup -4/), while its complexity is lower.     

Adaptive source-channel subband video coding for wireless channels

This paper presents a general framework for combined source-channel coding within the context of subband coding. The unequal importance of subbands in reconstruction of the source is exploited by an appropriate allocation of source and channel coding rates for the coding and transmission of subbands over a noisy channel. For each subband, the source coding rate as well as the level of protection (quantified by the channel coding rate) are jointly chosen to minimize the total end-to-end mean-squared distortion suffered by the source. This allocation of source and channel coding rates is posed as a constrained optimization problem, and solved using a generalized bit allocation algorithm. The optimal choice of source and channel coding rates depends on the state of the physical channel. These results are extended to transmission over fading channels using a finite state model, where every state corresponds to an additive white Gaussian noise (AWGN) channel. A coding strategy is also developed that minimizes the average distortion when the channel state is unavailable at the transmitter. Experimental results are provided that demonstrate application of these combined source-channel coding strategies on video sequences     

On the joint source-channel decoding of variable-length encodedsources: the BSC case

This paper proposes an optimal maximum a posteriori probability decoder for variable-length encoded sources over binary symmetric channels (BSC) that uses a novel state-space to deal with the problem of variable-length source codes in the decoder. This sequential, finite-delay, joint source-channel decoder delivers substantial improvements over the conventional decoder and also over a system that uses a standard forward error correcting code operating at the same over all bit rates. This decoder is also robust to inaccuracies in the estimation of channel statistics     

On joint source-channel coding for the Wyner-Ziv source and the Gel'fand-Pinsker channel

We consider the problem of lossy joint source-channel coding in a communication system where the encoder has access to channel state information (CSI) and the decoder has access to side information that is correlated to the source. This configuration combines the Wyner-Ziv (1976) model of pure lossy source coding with side information at the decoder and the Shannon/Gel'fand-Pinsker (1958, 1980) model of pure channel coding with CSI at the encoder. We prove a separation theorem for this communication system, which asserts that there is no loss in asymptotic optimality in applying, first, an optimal Wyner-Ziv source code and, then, an optimal Gel'fand-Pinsker channel code. We then derive conditions for the optimality of a symbol-by-symbol (scalar) source-channel code, and demonstrate situations where these conditions are met. Finally, we discuss a few practical applications, including overlaid communication where the model under discussion is useful.     

Design of Systematic Unequal Error Protection Raptor Codes Over Binary Erasure Channels

The third generation partnership project (3GPP) and digital video broadcasting-handheld standards recommend systematic Raptor codes as application-layer forward error correction for reliable transmission of multimedia data. In all previous studies on systematic Raptor codes, equal error protection for all data was considered. However, in many applications, multimedia data requires unequal error protection (UEP) that provides different levels of protection to different parts of multimedia data. In this paper, we propose a new design method for Raptor codes that provide both UEP and systematic properties over binary erasure channels. Numerical results show that the proposed UEP design is effective for reliable multi-level protection.     

Distributed video coding based on lossy syndromes generated in hybrid pixel/transform domain

A recently proposed class of distributed source coding based video coders enables low-complexity compression and robust transmission over unreliable channels. These architectures process the video signal either in the pixel or in the transform domain generating some side information that permits a correct decoding of the coded image from a set of possible correlated sources. The approach proposed in this paper processes the video sequence both in the pixel and in the transform domain exploiting the advantages of both schemes and generating a set of lossy syndromes. The resulting video coding scheme requires a lower computational complexity at the decoder with respect to their transform-domain counterparts (like DISCOVER or PRISM) and provides a high compression gain and an increased robustness against channel losses.