The use of scalable video with layered multicast has been shown to be an effective method to achieve rate control in heterogeneous networks. In this paper, we propose the use of layered FEC as an error control mechanism in a layered multicast framework. By organizing FEC into multiple lay-ers, receivers can obtain different levels of protection commensurate with their respective channel conditions. Efficient network utilization is achieved as FEC streams are multicast, and only to receivers that need them. Furthermore, FEC is used without overall rate expansion by selectively dropping data layers to make room for FEC layers. Effects of bursty losses are amortized by stag-gering the FEC streams in time, giving rise to a trade-off between delay and quality. For rate control at the receivers, we propose an equation-based approach that computes network usage as a function of measured network characteristics. We show that equation-based rate control achieves more fair bandwidth sharing amongst competing sessions as compared to existing multicast rate con-trol schemes such as RLM and RLC. Fairness is achieved since competing sessions sharing a path will measure similar network characteristics. Simulations and actual MBONE experiments are per-formed using error-resilient, scalable video compression. We find that video quality is significantly improved at the same communication rate when layered FEC is used. 1

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 jo...

Video transport over error-prone channels may result in loss or erroneous decoding of the video. Error concealment is an effective mechanism to reconstruct the video content. In this paper, we review different error concealment methods and introduce a new framework, which we refer to as second-generation error concealment. All the error concealment methods reconstruct the lost video content by making use of some a priori knowledge about the video content. First generation error concealment builds such a priori in a heuristic manner. The proposed second-generation error concealment builds the a priori by modeling the statistics of the video content. Context-based models are trained with the correctly decoded video content, and then used to replenish the lost video content. Trained models capture the statistics of the video content and thus reconstruct the lost video content better than reconstruction by heuristics.

Abstract — An approach to optimal soft decoding for vector quantization (VQ) over a code-division multiple-access (CDMA) channel is presented. The decoder of the system is soft in the sense that the unquantized outputs of the matched filters are utilized directly for decoding (no decisions are taken), and optimal according to the minimum mean-squared error (MMSE) criterion. The derived decoder utilizes a priori source information and knowledge of the channel characteristics to combat channel noise and multiuser interference in an optimal fashion. Hadamard transform representations for the user VQ’s are employed in the derivation and for the implementation of the decoder. The advantages of this approach are emphasized. Suboptimal versions of the optimal decoder are also considered. Simulations show the soft decoders to outperform decoding based on maximum-likelihood (ML) multiuser detection. Furthermore, the suboptimal versions are demonstrated to perform close to the optimal, at a significantly lower complexity in the number of users. The introduced decoders are, moreover, shown to exhibit near–far resistance. Simulations also demonstrate that combined source–channel encoding, with joint source–channel and multiuser decoding, can significantly outperform a tandem source–channel coding scheme employing multiuser detection plus table lookup source decoding. Index Terms—Code-division multiple access, combined source and channel coding, joint optimization, multiuser detection, multiuser systems, soft decoding, vector quantization. I.

We present in this paper an adaptive joint source-channel coding scheme using rate shaping on pre-coded video data. Rate shaping selectively drops portions of the video bitstream before transmitting them in order to satisfy the network bandwidth requirement. In wireless multimedia transport over heterogeneous networks, limited bandwidth is not the only issue. The high error rate of the channel should be considered as well, so channel coding is often applied. We propose a rate shaping method that drops not only the source-coding segments of the video bitstream, but also the channel-coding segments of the video bitstream, adaptively according to the network condition, in order to achieve the optimal rate-distortion performance. The proposed method is based on "discrete rate-distortion combination" to accomplish joint source-channel coding. We consider both the simulcast and multicast scenarios and show promising results.

Streaming of precoded video, which is both source and channel coded, over wireless networks faces challenges of time-varying packet loss rate and fluctuating bandwidth. Rate shaping has been proposed in [1] to "shape" the precoded video to adapt to the real-time bandwidth requirement and the packet loss rate. In this paper, we propose a novel "fine-grained rate shaping (FGRS)" scheme to allow for bandwidth adaptation over a wide range of bandwidth and packet loss rate. The video is precoded with fine granularity scalability (FGS) followed by forward error correction (FEC) coding with erasure codes. Utilizing the fine granularity property of FGS and FEC, FGRS selectively drops part of the precoded video and still yields decodable bitstream at the decoder. A new two-stage rate-distortion (R-D) optimization, with model-based hyper-plane and hill-climbing based refinement, is proposed to select part of the precoded video to drop. Promising results of FGRS are shown.

An iterative soft input soft output (SISO) decoding algorithm for Reed-Solomon (RS) codes using their binary image representations is presented. The novelty of the iterative algorithm is in reducing a submatrix corresponding to the less reliable bits in the binary parity check matrix of the RS code to a sparse nature before each decoding iteration. The proposed

Abstract — Streaming of video, which is both source- and channel- coded, over wireless networks faces the challenge of time-varying packet loss rate and fluctuating bandwidth. Rate shaping (RS) has been proposed to reduce the bit rate of a precoded video bitstream to adapt to the real-time bandwidth variation. In our earlier work, rate shaping was extended to consider not only the bandwidth but also the packet loss rate variations. Rate-distortion optimized rate adaptation is performed on the precoded video that is a scalable coded bitstream protected by forward error correction codes. In this paper, we propose a rate shaping scheme that further takes into account the error concealment (EC) method used at the receiver. We refer to this scheme as EC aware RS (ECARS). When performing ECARS, first ECARS needs to know the benefit/gain of sending each part of the precoded video, as opposed to not sending it but reconstructing it by EC. Then given a certain packet loss probability, the expected gain can be derived and be included in the rate-distortion optimization problem formulation. Finally ECARS performs rate-distortion optimization to adapt the rate of the precoded video. A two-stage rate-distortion optimization approach is proposed to solve the ECARS rate-distortion optimization problem. In addition to ECARS, the precoding process can be EC aware to prioritize the precoded video based on the gain. We present an example EC aware precoding process by means of macroblock prioritization. Experiment results of ECARS together with EC aware precoding are shown to have excellent performance. Index Terms —rate shaping, error concealment, rate-distortion optimization, wireless video

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Streaming of precoded video, which is both source- and channelcoded, over packet-loss networks faces challenges of the timevarying packet loss rate and fluctuating bandwidth. Rate shaping has been proposed to reduce the bit rate of a precoded video bitstream to adapt to the real-time bandwidth variation. In our earlier work, rate shaping was extended to consider not only the bandwidth but also the packet loss rate variations. In practice, the reconstructed result of the previous frame will affect the following frames if the video is predictive coded, and/or the error concealment method performed at the receiver utilizes temporal information.