Rapid growth of machine-type communications devices challenges the future network with a significant aggregated data traffic. distributed source coding is a promising technique that compresses data sources and decreas...
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Rapid growth of machine-type communications devices challenges the future network with a significant aggregated data traffic. distributed source coding is a promising technique that compresses data sources and decreases required aggregated data transmission rate. In this article, we discuss the merits and demerits of deploying distributed source coding in machine-type communications uplink transmissions. We analyze how the decoding delay and storage consumption scale with the number of users and prove that the average decoding delay grows linearly with the user number under some assumptions. A machine-type communications uplink transmission scheme adopting clustered distributed source coding is proposed to balance the compression ratio and decoding delay of distributed source coding where users are divided into independently encoded and decoded clusters. We evaluate three clustering algorithms, grid dividing, Weighted Pair Group Method with Arithmetic Mean, and K-medoids in our system model. The grid dividing algorithm clusters users based on their locations, while Weighted Pair Group Method with Arithmetic Mean and K-medoids cluster users using the correlation intensity between them. Our simulation results show that Weighted Pair Group Method with Arithmetic Mean and K-medoids outperform grid dividing on compression ratio and K-medoids and grid dividing have a more balanced delay distribution among different clusters than Weighted Pair Group Method with Arithmetic Mean.
In this letter, distributed source coding with one distortion criterion and correlated messages is considered. This problem can be regarded as "Berger-Yeung problem with correlated messages". It corresponds ...
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In this letter, distributed source coding with one distortion criterion and correlated messages is considered. This problem can be regarded as "Berger-Yeung problem with correlated messages". It corresponds to the sourcecoding part of the graph-based framework for transmission of a pair of correlated sources over the multiple-access channel where one is lossless and the other is lossy. As a result, the achievable rate-distortion region for this problem is provided. A rigorous proof of both achievability and converse part is also given.
Specific to the lower power efficiency of node in wireless sensor network (WSN), a residual value coding algorithm is raise for clustering WSNs, which is based on distributedsource encoding system. Theoretical analys...
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Specific to the lower power efficiency of node in wireless sensor network (WSN), a residual value coding algorithm is raise for clustering WSNs, which is based on distributedsource encoding system. Theoretical analysis and experimental result indicate if this algorithm could be adopted in clustering WSN, then it would reduce the transferred data of node effectively. Thus, the power consumption of network would go down drastically.
In this work, we consider a distributed source coding problem with a joint distortion criterion depending on the sources and the reconstruction. This includes as a special case the problem of computing a function of t...
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ISBN:
(纸本)9781424429257
In this work, we consider a distributed source coding problem with a joint distortion criterion depending on the sources and the reconstruction. This includes as a special case the problem of computing a function of the sources to within some distortion and also the classic Slepian-Wolf problem [12], Berger-Tung problem [5], Wyner-Ziv problem [4], Yeung-Berger problem [6] and the Ahlswede-Korner-Wyner problem [3], [13]. While the prevalent trend in information theory has been to prove achievability results using Shannon's random coding arguments, using structured random codes offer rate gains over unstructured random codes for many problems. Motivated by this, we present a new achievable rate-distortion region (an inner bound to the performance limit) for this problem for discrete memoryless sources based on "good" structured random nested codes built over abelian groups. We demonstrate rate gains for this problem over traditional coding schemes using random unstructured codes. For certain sources and distortion functions, the new rate region is strictly bigger than the Berger-Tung rate region, which has been the best known achievable rate region for this problem till now. Further, there is no known unstructured random coding scheme that achieves these rate gains. Achievable performance limits for single-user sourcecoding using abelian group codes are also obtained as parts of the proof of the main coding theorem. As a corollary, we also prove that nested linear codes achieve the Shannon rate-distortion bound in the single-user setting. Note that while group codes retain some structure, they are more general than linear codes which can only be built over finite fields which are known to exist only for certain sizes.
Because of differential coding used in standard video compression algorithms to exploit temporal correlation in adjacent frames for coding gain, a frame lost in network will cause error propagation in subsequent frame...
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ISBN:
(纸本)9781457720536
Because of differential coding used in standard video compression algorithms to exploit temporal correlation in adjacent frames for coding gain, a frame lost in network will cause error propagation in subsequent frames at the decoder. Previously proposed distributed source coding (DSC) frames can be periodically inserted to halt this error propagation by overcoming the uncertainty at encoder of which frames will be correctly received at decoder, without resorting to large intra-coded I-frames. In the case of interactive multiview video streaming (IMVS), where a user watches one of M available captured views at a time but can periodically select and switch to a neighboring view, the encoder must encode multiview video to enable this view-switching interactivity without knowing the exact view trajectories taken by viewers at stream time. In this paper, we propose a unified DSC frame construction for IMVS, so that the encoder can overcome both types of uncertainty in a coding-efficient manner;i.e., halt error propagation in differentially coded multiview video and facilitate periodic interactive view-switching at the same time. Having the additional unified DSC frames, we design a multiview frame structure to maximize the expected number of correctly decoded frames at decoder for a given bandwidth constraint. We develop a fast algorithm to find locally optimal structure parameters, and packetization and packet reordering strategies for transmission. Experimental results show that our optimized frame structures using unified DSC frames outperform naive structures using I-and P-frames only by up to 49% in fraction of correctly decoded frames under typical network condition.
This paper presents an efficient compression algorithm based on distributed source coding. The proposed algorithm employs a block-based quantizer followed by distributed lossless coding. First, a bit-rate allocation a...
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ISBN:
(纸本)9781510817982
This paper presents an efficient compression algorithm based on distributed source coding. The proposed algorithm employs a block-based quantizer followed by distributed lossless coding. First, a bit-rate allocation algorithm is used to assign the rational bit-rate for each block. Subsequently, the multi-linear regression model is employed to construct the side information of each block, and the optimal quantization step size of each block is obtained under the assigned bit-rate while minimizing the distortion. Finally, the quantized block is encoded by distributed lossless compression. Experimental results show that the proposed algorithm provides competitive compression performance, low encoder complexity and error resilience.
This paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all ...
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This paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all sources. The problem involves a joint consideration of distributed compression and network information relaying. Although the optimal rate region has been theoretically characterized, it was not clear how to design practical communication schemes with low complexity. This work provides a partial solution to this problem by proposing a low-complexity scheme for the special case with two sources whose correlation is characterized by a binary symmetric channel. Our scheme is based on a careful combination of linear syndrome-based Slepian-Wolf coding and random linear mixing (network coding). It is in general suboptimal, however, its low complexity and robustness to network dynamics make it suitable for practical implementation.
A distributed joint source-channel coding scheme based on a unity-rate code (URC) assisted trellis coded modulation (TCM) is proposed, which exploits the spatiotemporal correlation of symbol-based sources. More specif...
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A distributed joint source-channel coding scheme based on a unity-rate code (URC) assisted trellis coded modulation (TCM) is proposed, which exploits the spatiotemporal correlation of symbol-based sources. More specifically, asymmetric distributed source coding of two spatially correlated Markov sources is considered, where one of the sources is assumed to be perfectly decoded and to be available at the receiver of the other source as side information. In order to exploit the temporal correlation statistics, an iterative decoding process exchanging extrinsic information between the amalgamated URC-assisted TCM and a soft-symbol source decoder employing a modified symbol-based maximum a posteriori algorithm is invoked. Furthermore, the Slepian-Wolf (SW) bound of symbol-based sources having spatiotemporal correlation is derived and the benefits of exploiting the spatiotemporal correlation using the proposed coding scheme are demonstrated by our extrinsic information transfer chart analysis. It is shown from our simulation results that upon exploiting the spatiotemporal correlation of the sources, the proposed coding scheme is capable of operating within 0.02 b of the SW bound.
In this paper,we analyze the rate-distortion(R-D) performance of distributed source coding(DSC) *** W-Z problem,quantization must consider source,channel,side *** variable cases,source and output of quantization and s...
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In this paper,we analyze the rate-distortion(R-D) performance of distributed source coding(DSC) *** W-Z problem,quantization must consider source,channel,side *** variable cases,source and output of quantization and side information forming different Markov chain,we propose rate distortion functions for clean and noisy sources using these *** on these functions,we analyze some system parameters related to R-D performance for Gaussian *** results show that side information have obviously effect.
The genome sequence compression algorithm based on the distributed source coding technology purely is proposed in this paperIn order to enhance the compression efficiency, the genome sequence is mapped into two binary...
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The genome sequence compression algorithm based on the distributed source coding technology purely is proposed in this paperIn order to enhance the compression efficiency, the genome sequence is mapped into two binary sources and then they are transmitted into two bilevel imagesAfter initialization, the distributed source coding based on LDPC is constructed for compressing these two sequencesTo compress the side information, the optimized context weighting is suggestedThe experiments results indicate that the coding efficiency is better than results from any other compression algorithms for microbial genome sequence compression.
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