In this paper, a novel trellis source encoding scheme based on punctured ring convolutional codes is presented. joint source and channel coding (JSCC) using trellis coded Continuous Phase Modulation (CPM) with punctur...
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In this paper, a novel trellis source encoding scheme based on punctured ring convolutional codes is presented. joint source and channel coding (JSCC) using trellis coded Continuous Phase Modulation (CPM) with punctured convolutional codes over rings is investigated. The channels considered are the Additive White Gaussian Noise (AWGN) channel and the Rayleigh fading channel. Optimal soft decoding for the proposed JSCC scheme is studied. The soft decoder is based on the A Posteriori Probability (APP) algorithm for trellis coded CPM with punctured ring convolutional codes. It is shown that these systems with soft decoding outperform the same systems with hard decoding especially when the systems operate at low to medium Signal-to-Noise Ratio (SNR). Furthermore adaptive JSCC approaches based on the proposed sourcecoding scheme are investigated. Compared with JSCC schemes with fixed sourcecoding rates, the proposed adaptive approaches can achieve much better performance in the high SNR region. The novelties of this work are the development of a trellis source encoding method based on punctured ring convolutional codes, the use of a soft decoder, the APP algorithm for the combined systems and the adaptive approaches to the JSCC problem.
Three-dimensional graphic scenes contain various mesh objects in one geometric space where different objects have potentially unequal importance regarding display. This paper proposes an object-oriented system for eff...
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Three-dimensional graphic scenes contain various mesh objects in one geometric space where different objects have potentially unequal importance regarding display. This paper proposes an object-oriented system for efficiently coding and streaming 3-D scene databases in lossy and rate-constrained environments. Vector quantization (VQ) is exploited to code 3-D scene databases into multiresolution hierarchies. For the best distortion-rate performance, adaptive quantization precisions are allocated to different objects and different layers of each object based on a weighted distortion model. Upon transmission, scalably coded objects are delivered in respective packet sequences to preserve their manipulation independency. For packet loss resilience, a plurality of FEC codes are generated as "parity objects" parallel to graphic objects, which protect the graphic objects concurrently and also preferentially in regard to their unequal decoding importance. A rate-distortion optimization framework is then developed, which performs rate allocation between graphic objects and parity objects and generates the parity data properly. We show that, by treating graphic objects jointly and preferentially in source and channelcoding while preserving their independencies in transport, the proposed system reduces the receiving distortion of the 3-D database significantly compared to conventional methods.
In this letter, a double polar code (D-Polar) for joint source and channel coding (JSCC) is proposed, in which the source compress is implemented by a polar code, the channel error correction is performed by a systema...
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In this letter, a double polar code (D-Polar) for joint source and channel coding (JSCC) is proposed, in which the source compress is implemented by a polar code, the channel error correction is performed by a systematic polar code. Furthermore, a turbo-like belief propagation (TL-BP) decoder consisted of a channel BP decoder and a source BP decoder is proposed for jointsource and channel decoding in the receiver. In this TL-BP decoder, the soft information is exchanged between the channel BP decoder and the source BP decoder so as to improve the efficiency of channel decoding in utilizing the source information residual in the compressed bits. Simulation results show that the performance of the proposed D-Polar JSCC scheme with TL-BP decoder is significantly improved compared with the existing source-channeljoint polarization scheme.
In this paper, the joint source and channel coding for progressive image transmission over channels with varying SNR is considered. Since the feedback of channel status information generally lags behind the channel va...
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ISBN:
(纸本)9781424403523
In this paper, the joint source and channel coding for progressive image transmission over channels with varying SNR is considered. Since the feedback of channel status information generally lags behind the channel variation and the optimization process often causes high computational complexity, it is appropriate to optimally allocate the given bandwidth between the source and channel codes based on the statistics of the channel rather than a specific SNR. In such case, the optimization objective function is no longer in a recursive format and the computational complexity with exhaustive search for the optimal allocation is prohibitive. In this paper, we present a simple yet very effective genetic algorithm (GA) based optimization method so that the near-optimal channel rate allocation can be obtained through crossover and mutation operations over a candidate pool. Simulation shows that this GA-based method always approaches to the optimal results or the brute force search for the considered scenario, but with much lower complexity.
In this paper we propose a novel Irregular Variable Length coding (IrVLC) scheme for near-capacity joint source and channel coding. We employ a number of component Variable Length coding (VLC) codebooks having differe...
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In this paper we propose a novel Irregular Variable Length coding (IrVLC) scheme for near-capacity joint source and channel coding. We employ a number of component Variable Length coding (VLC) codebooks having different coding rates for encoding particular fractions of the input source symbol stream. These fractions may be chosen with the aid of EXtrinsic Information Transfer (EXIT) charts in order to shape the inverted EXIT curve of the IrVLC codec for ensuring that it does not cross the EXIT curve of a serially concatenated channel codec. In this way, an open EXIT chart tunnel may be created even at low E-b/N-0 values that are close to the capacity bound of the channel. We propose iteratively decoded serially concatenated IrVLC designs amalgamated with Trellis Coded Modulation (TCM). These schemes are shown to be capable of operating within 0.6 dB of the uncorrelated narrowband Rayleigh fading channel's capacity bound using an average interleaver length of 217,500 bits and an effective bandwidth efficiency of 1.56 bit/s/Hz, assuming ideal Nyquist filtering. By contrast, the equivalent-rate regular VLC-based bench-marker schemes were found to be capable of operating at a higher distance of 1.1 dB from the capacity bound, which is nearly twice that of the proposed IrVLC-TCM scheme. Additionally, an Irregular Convolutional coding (IrCC) based bench-marker was found to be capable of operating at 0.8 dB from the capacity bound, owing to its slightly eroded performance when operating with the considered interleaver length.
This paper presents a joint source and channel coding method for transmission of progressively, compressed three-dimensional (3-D) models where the bit budget is allocated optimally. The proposed system uses the Compr...
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This paper presents a joint source and channel coding method for transmission of progressively, compressed three-dimensional (3-D) models where the bit budget is allocated optimally. The proposed system uses the Compressed Progressive Mesh (CPM) algorithm to produce a hierarchical bitstream representing different levels of detail (LODs). In addition to optimizing the transmitted bitstream with respect to the channel characteristics, we also choose the optimum combination of quantization and tessellation to maximize the expected decoded,model quality. That is, given a 3-D mesh, a total bit budget (B) and a channel packet-loss rate (P-LR), we determine the optimum combination of: 1) the geometry coordinates quantizer step size (l-bit);2) the number of transmitted batches (L);3) the total number of channelcoding bits (C);and 4) the distribution of these channelcoding bits among the transmitted levels (C-L). Experimental results show that, with our unequal error-protection approach that uses the proposed bit-allocation algorithm, the decoded model quality degrades more gracefully (compared to either no error protection or equal error protection methods) as the packet-loss rate increases.
joint source and channel coding (JSCC) using trellis coded quantization (TCQ) in conjunction with trellis coded continuous phase modulation (CPM) is studied. The channel is assumed to be the additive white gaussian no...
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joint source and channel coding (JSCC) using trellis coded quantization (TCQ) in conjunction with trellis coded continuous phase modulation (CPM) is studied. The channel is assumed to be the additive white gaussian noise (AWGN) channel. Analytical bounds on the channel distortion for the investigated systems with maximum-likelihood sequence detection (MLSD) are developed. The bounds are based on the transfer function technique, which was modified and generalized to include continuous-amplitude discrete-time signals. For a memoryless;uniform source, the constructed bounds for the investigated systems are shown to be asymptotically tight for increasing channel signal-to-noise ratio (SNR) values. For a memoryless nonuniform source, the constructed bounds are not as tight as the one for the uniform source, however, it still can be used as an indication to how the system performs. It is concluded that the minimum Euclidean distance of the system alone is not enough to evaluate the performance of the considered systems. The number of error events having minimum Euclidean distance and the total distortion caused by those error events also affect the asymptotic performance. This work provides an analysis tool for the investigated systems. The analysis method is very general. It may be applied to any trellis based JSCC schemes. Index
joint source and channel coding (JSCC) has attracted increasing attention in semantic communications. However, JSCC is vulnerable to privacy issues due to the high relevance between the source image and channel input....
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joint source and channel coding (JSCC) has attracted increasing attention in semantic communications. However, JSCC is vulnerable to privacy issues due to the high relevance between the source image and channel input. In this paper, we propose a disentangled information bottleneck guided privacy-protective JSCC (DPJSCC) for image transmission, which aims at protecting private information and achieving superior image transmission performance. In particular, we propose a disentangled information bottleneck objective to compress the private information in public subcodewords and improve the reconstruction quality simultaneously. To optimize JSCC neural networks using the proposed objective, we derive a differentiable estimation based on variational approximation and the density-ratio trick. Additionally, we design a password-based privacy-protective algorithm that encrypts the private subcodewords, achieving joint optimization with JSCC neural networks. The proposed algorithm involves an encryptor for encrypting private information and a decryptor for recovering it at the legitimate receiver. A loss function is derived based on the maximum entropy principle for jointly training the encryptor, decryptor, and JSCC decoder to maximize eavesdropping uncertainty and improve reconstruction quality. Experimental results show that DPJSCC reduces eavesdropping accuracy on private information by up to 18% and decreases inference time by 10%.
joint source and channel coding (JSCC) for image transmission has attracted increasing attention due to its robustness and high efficiency. However, the existing deep JSCC research mainly focuses on minimizing the dis...
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joint source and channel coding (JSCC) for image transmission has attracted increasing attention due to its robustness and high efficiency. However, the existing deep JSCC research mainly focuses on minimizing the distortion between the transmitted and received information under a fixed number of available channels. Therefore, the transmitted rate may be far more than its required minimum value. In this paper, an adaptive information bottleneck (IB) guided joint source and channel coding (AIB-JSCC) method is proposed for image transmission. The goal of AIB-JSCC is to reduce the transmission rate while improving the image reconstruction quality. In particular, a new IB objective for image transmission is proposed so as to minimize the distortion and the transmission rate. A mathematically tractable lower bound on the proposed objective is derived, and then, adopted as the loss function of AIB-JSCC. To trade off compression and reconstruction quality, an adaptive algorithm is proposed to adjust the hyperparameter of the proposed loss function dynamically according to the distortion during the training. Experimental results show that AIB-JSCC can significantly reduce the required amount of transmitted data and improve the reconstruction quality and downstream task accuracy.
In this paper, we first propose an adaptation scheme at each source for adjusting send rates and channel code ratios of all flows at each source by using a joint source and channel coding based approach. Sufficient co...
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ISBN:
(纸本)9781424450466
In this paper, we first propose an adaptation scheme at each source for adjusting send rates and channel code ratios of all flows at each source by using a joint source and channel coding based approach. Sufficient conditions are derived for formulating such a challenging problem as a convex optimization problem. A simple algorithm is provided to solve this problem. We then design a simple scheduling algorithm for transmitting packets from all flows at each link by using a weighted round robin based method. The proposed adaptation scheme at each source and the scheduling algorithm at each link form a framework for real time video applications over the Internet. With the proposed framework, Internet service providers (ISPs) have incentive to increase their capacities so that the Internet is more friendly to high bandwidth consuming applications such as real time video applications over the Internet.
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