Design of sample adaptive product quantizers for noisy channels

Channel-optimized vector quantization (COVQ) has proven to be an effective joint source-channel coding technique that makes the underlying quantizer robust to channel noise. Unfortunately, COVQ retains the high encoding complexity of the standard vector quantizer (VQ) for medium-to-high quantization dimensions and moderate-to-good channel conditions. A technique called sample adaptive product quantization (SAPQ) was recently introduced by Kim and Shroff to reduce the complexity of the VQ while achieving comparable distortions. In this letter, we generalize the design of SAPQ for the case of memoryless noisy channels by optimizing the quantizer with respect to both source and channel statistics. Numerical results demonstrate that the channel-optimized SAPQ (COSAPQ) achieves comparable performance to the COVQ (within 0.2 dB), while maintaining considerably lower encoding complexity (up to half of that of COVQ) and storage requirements. Robustness of the COSAPQ system against channel mismatch is also examined.     

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     

噪声信道中基于进化算法的矢量量化器的设计

本文提出了一个基于进化算法的信道最优矢量量化器（COVQ）设计算法。该算法在给定信道状态模型和存在信道噪声的情况下，可以有效地提高矢量量化器的性能，实现了信道最优矢量量化器的设计。与目前常用的码书设计算法比较，实验结果表明该算法可获得比传统算法更高的性能增益。     

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.     

Soft-decision COVQ for Rayleigh-fading channels

A channel-optimized vector quantizer (COVQ) scheme that exploits the channel soft-decision information is proposed. The scheme is designed for stationary memoryless Gaussian and Gauss-Markov sources transmitted over BPSK-modulated Rayleigh-fading channels. It is demonstrated that substantial coding gains of 2-3 dB in channel signal-to-noise ratio (SNR) and 1-1.5 dB in source signal-to-distortion ratio (SDR) can be achieved over COVQ systems designed for discrete (hard-decision demodulated) channels     

Weighted universal image compression

We describe a general coding strategy leading to a family of universal image compression systems designed to give good performance in applications where the statistics of the source to be compressed are not available at design time or vary over time or space. The basic approach considered uses a two-stage structure in which the single source code of traditional image compression systems is replaced with a family of codes designed to cover a large class of possible sources. To illustrate this approach, we consider the optimal design and use of two-stage codes containing collections of vector quantizers (weighted universal vector quantization), bit allocations for JPEG-style coding (weighted universal bit allocation), and transform codes (weighted universal transform coding). Further, we demonstrate the benefits to be gained from the inclusion of perceptual distortion measures and optimal parsing. The strategy yields two-stage codes that significantly outperform their single-stage predecessors. On a sequence of medical images, weighted universal vector quantization outperforms entropy coded vector quantization by over 9 dB. On the same data sequence, weighted universal bit allocation outperforms a JPEG-style code by over 2.5 dB. On a collection of mixed test and image data, weighted universal transform coding outperforms a single, data-optimized transform code (which gives performance almost identical to that of JPEG) by over 6 dB.     

信道最优的变换编码--联合信源信道编码的一种新方法

简要介绍Shannon分离理论的优缺点，并由此引入对联合信源信道编码的介绍，重点对联合信源信道编码方法中的信道最优的变换编码方法进行了论述，同时也对信道最优的变换编码的设计及其性能进行了介绍。     

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.     

Progressive source coding for a power constrained Gaussian channel

We consider the progressive transmission of a lossy source across a power constrained Gaussian channel using binary phase-shift keying modulation. Under the theoretical assumptions of infinite bandwidth, arbitrarily complex channel coding, and lossless transmission, we derive the optimal channel code rate and the optimal energy allocation per transmitted bit. Under the practical assumptions of a low complexity class of algebraic channel codes and progressive image coding, we numerically optimize the choice of channel code rate and the energy per bit allocation. This model provides an additional degree of freedom with respect to previously proposed schemes, and can achieve a higher performance for sources such as images. It also allows one to control bandwidth expansion or reduction     

On source coding, channel coding and spreading tradeoffs in a DS-CDMA system operating over frequency selective fading channels with narrowband interference

For a fixed total bandwidth expansion factor, we consider the problem of optimal bandwidth allocation among the source coder, the channel coder, and the spread-spectrum unit for a direct-sequence code-division multiple-access system operating over a frequency-selective fading channel with narrowband interference. Assuming a Gaussian source with the optimum scalar quantizer, and a binary convolutional code with soft-decision decoding, and further assuming that the self-interference is negligible, we obtain both a lower and an upper bound on the end-to-end average source distortion. The joint three-way constrained optimization of the source code rate, the channel code rate, and the spreading factor can be simplified into an unconstrained optimization problem over two variables. Upon fixing the channel code rate, we show that both upper and lower bound-based distortion functions are convex functions of the source code rate. Because an explicit solution for the optimum source code rate, i.e., one that minimizes the average distortion, is difficult to obtain, computer-based search techniques are employed. Numerical results are presented for the optimum source code rate and spreading factor, parameterized by the channel code rate and code constraint length. The optimal bandwidth allocation, in general, depends on the system and the channel conditions, such as the total number of active users, the average jammer-to-signal power ratio, and the number of resolved multipath components together with their power delay profile.     

Unequal error protection for MPEG-2 video transmission over wireless channels

This paper proposes an unequal error protection (UEP) method for MPEG-2 video transmission. Since the source and channel coders are normally concatenated, if the channel is noisy, more bits are allocated to channel coding and fewer to source coding. The situation is reversed when the channel conditions are more benign. Most of the joint source channel coding (JSCC) methods assume that the video source is subband coded, the bit error sensitivity of the source code can be modeled, and the bit allocations for different subband channels will be calculated. The UEP applied to different subbands is the rate compatible punctured convolution channel coder. However, the MPEG-2 coding is not a subband coding, the bit error sensitivity function for the coded video can no longer be applied. Here, we develop a different method to find the rate-distortion functions for JSCC of the MPEG-2 video. In the experiments, we show that the end-to-end distortion of our UEP method is smaller than the equal error protection method for the same total bit-rate.     

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 unequal error protection for progressive image transmission.

In this paper, we consider the unequal error protection (UEP) for progressive image transmission when the coded packet size is fixed. First, we prove that, for the source code with convex rate-distortion (R-D) function and practically used channel codes, the channel code rate for each packet in the optimal rate allocation is nondecreasing indeed. Then, we give an upper bound for the channel code rate of the last packet so that the number of rate allocations in the exhaustive search can be predicted. Further, we propose a heuristic optimization method which has low complexity and obtains performance approaching to the optimal solutions for various channel conditions and transmission rates.     

Robust JPEG image transmission using unequal error protection and code combining

JPEG image transmission over noisy channels is highly problematic due to the sensitivity of the JPEG bit stream to error propagation. The use of resynchronization markers and channel coding do not alleviate the problem completely thus making retransmissions inevitable. In packetized image transmission, image packets are repeated n times, to ensure reliable transmission. This paper proposes a new unequal error protection (UEP) scheme which jointly optimizes the allocation of channel code rates and number of repeats to image packets, subject to a constraint on the maximum overall transmission rate. The coding scheme used is the rate compatible punctured convolutional code coupled with the code‐combining technique. An unequal allocation of headers to the image packets is also performed in order to reduce the overall distortion due to error propagation. Simulation results show that the proposed UEP scheme provides a gain of more than 8 dB in peak‐to‐peak signal‐to‐noise ratio over a tandem scheme. The flexibility of the proposed scheme, and the major performance gains obtained, make the scheme appealing for applications like, web‐based image browsing, multi‐hop networks, and wireless image transmission. Copyright © 2007 John Wiley & Sons, Ltd.     

Optimal resource allocation for Medium Grain Scalable video transmission over MIMO channels

In this paper we investigate an optimal solution for adaptive H.264/SVC video transmission over Multiple-Input Multiple-Output (MIMO) channels.We first write the end-to-end distortion of the H.264/SVC video transmission over a diagonal MIMO channel. The total distortion is expressed following three physical layer parameters: power allocation, modulation spectral efficiency and Error Code Correction (ECC) code rate. Minimizing the total distortion is considered as an optimization problem containing both discrete and continuous variables.We use the Lagrangian method associated with Karush–Kuhn and Tucker conditions to find out the optimal continuous physical layer parameters. Concerting the discrete modulation spectral efficiency and ECC code rate, we exploit information of the MIMO system to remove all suboptimal configurations. Therefore, the optimal power allocation is computed only for a reduced number of discrete configurations.The performance of the proposed solution is evaluated over both statistical and realistic MIMO channels. Results show that the proposed solution performs an optimal resource allocation to achieve the best QoS regardless the channel conditions.     

基于RS的IP网络视频JSCC策略研究

针对IP网络视频通信中数据分组丢失严重影响视频通信质量的问题,引入具有良好抗分组丢失性能的RS信道编码方法,在深入分析基于RS码的网络环境下的端到端视频传输失真基础上,提出了一种基于RS码的IP网络环境下的网络视频信源信道联合编码(JSCC,joint source channel coding)方案,该方案可以根据当...     

The design of joint source and channel trellis waveform coders

The generalized Lloyd algorithm is applied to the design of joint source and channel trellis waveform coders to encode discrete-time continuous-amplitude stationary and ergodic sources operating over discrete memoryless noisy channels. Experimental results are provided for independent and autoregressive Gaussian sources, binary symmetric channels, and absolute error and squared error distortion measures. Performance of the joint codes is compared with the tandem combination of a trellis source code and a trellis channel code on the independent Gaussian source using the squared error distortion measure operating over an additive white Gaussian noise channel. It is observed that the jointly optimized codes achieve performance close to or better than that of separately optimized tandem codes of the same constraint length. Performance improvement via a predictive joint source and channel trellis code is demonstrated for the autoregressive Gaussian source using the squared error distortion measure.     

Multiuser Distortion Management of Layered Video over Resource Limited Downlink Multicode-CDMA

Transmitting multiple real-time encoded videos to multiple users over wireless cellular networks is a key driving force for developing broadband technology. We propose a new framework to transmit multiple users' video programs encoded by MPEG-4 FGS codec over downlink multicode CDMA networks in real time. The proposed framework jointly manages the rate adaptation of source and channel coding, CDMA code allocation, and power control. Subject to the limited system resources, such as the number of pseudo-random codes and the maximal power for CDMA transmission, we develop an adaptive scheme of distortion management to ensure baseline video quality for each user and further reduce the overall distortion received by all users. To efficiently utilize system resources, the proposed scheme maintains a balanced ratio between the power and code usages. We also investigate three special scenarios where demand, power, or code is limited, respectively. Compared with existing methods in the literature, the proposed algorithm can reduce the overall system's distortion by 14% to 26%. In the demand-limited case and the code-limited but power-unlimited case, the proposed scheme achieves the optimal solutions. In the power-limited but code-unlimited case, the proposed scheme has a performance very close to a performance upper bound     

Tradeoff between source and channel coding

A fundamental problem in the transmission of analog information across a noisy discrete channel is the choice of channel code rate that optimally allocates the available transmission rate between lossy source coding and block channel coding. We establish tight bounds on the channel code rate that minimizes the average distortion of a vector quantizer cascaded with a channel coder and a binary-symmetric channel. Analytic expressions are derived in two cases of interest: small bit-error probability and arbitrary source vector dimension; arbitrary bit-error probability and large source vector dimension. We demonstrate that the optimal channel code rate is often substantially smaller than the channel capacity, and obtain a noisy-channel version of the Zador (1982) high-resolution distortion formula     

Quantization of Multiple Sources Using Nonnegative Integer Bit Allocation

Asymptotically optimal real-valued bit allocation among a set of quantizers for a finite collection of sources was derived in 1963 by Huang and Schultheiss, and an algorithm for obtaining an optimal nonnegative integer-valued bit allocation was given by Fox in 1966. We prove that, for a given bit budget, the set of optimal nonnegative integer-valued bit allocations is equal to the set of nonnegative integer-valued bit allocation vectors which minimize the Euclidean distance to the optimal real-valued bit-allocation vector of Huang and Schultheiss. We also give an algorithm for finding optimal nonnegative integer-valued bit allocations. The algorithm has lower computational complexity than Fox's algorithm, as the bit budget grows. Finally, we compare the performance of the Huang-Schultheiss solution to that of an optimal integer-valued bit allocation. Specifically, we derive upper and lower bounds on the deviation of the mean-squared error (MSE) using optimal integer-valued bit allocation from the MSE using optimal real-valued bit allocation. It is shown that, for asymptotically large transmission rates, optimal integer-valued bit allocations do not necessarily achieve the same performance as that predicted by Huang-Schultheiss for optimal real-valued bit allocations