We present a,new source coding scheme with smaller expected length than Shannon-Fano-Elias codes. The ordering of source symbols input to the proposed encoding algorithm can be arbitrary. We show that this property le...
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We present a,new source coding scheme with smaller expected length than Shannon-Fano-Elias codes. The ordering of source symbols input to the proposed encoding algorithm can be arbitrary. We show that this property leads to exponential complexity for eavesdropping even though an adversary knows the code construction rule and the probability mass function of the source.
This paper investigates source compression for Indonesian local languanges and derives a closed-form expression of their outage probabilities using Slepian-Wolf coding theorem to observe their potential applications f...
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ISBN:
(纸本)9781538627785
This paper investigates source compression for Indonesian local languanges and derives a closed-form expression of their outage probabilities using Slepian-Wolf coding theorem to observe their potential applications for fifth generation (5G) services. The 5G services involving language compressions are, for example, hologram-based telephone services and voice command of self-driving car. We also propose labelling pattern for Indonesian local languages based on Huffman codes having expected length closes to the entropies of Sundanese, Javanese, and Balinese. To observe the compression level of Indonesian local languages, we also provide a comparison analysis of the outage probability to French and English as some representative examples of foreign languages. We found that Indonesian local languages have better compression rates and lower outage probability and are potential for future 5G applications involving language services.
We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate...
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We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.
We consider the lossy quantum source coding problem, where the task is to compress a given quantum source below its von Neumann entropy. Inspired by the duality connections between the rate-distortion and channel codi...
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We consider the lossy quantum source coding problem, where the task is to compress a given quantum source below its von Neumann entropy. Inspired by the duality connections between the rate-distortion and channel coding problems in the classical setting, we propose a new formulation for the lossy quantum source coding problem. This formulation differs from the existing quantum rate-distortion theory in two aspects. Firstly, we require that the reconstruction of the compressed quantum source fulfill a global error constraint as opposed to the sample-wise local error criterion used in the standard rate-distortion setting. Secondly, to measure the reconstruction error, instead of a distortion observable, we employ the notion of a backward quantum channel which we refer to as a "posterior reference map". Using these, we characterize the asymptotic performance limit in terms of single-letter coherent information of the given posterior reference map. We also develop analogous formulations for the quantum-classical and classical variants and characterize their asymptotic performance limits in terms of single-letter mutual information quantities with respect to appropriately defined channels analogous to the posterior reference map. We also provide various examples for the three formulations, and shed light on their connection to the standard rate-distortion formulation wherever possible.
We introduce two variants of the information spectrum relative entropy defined by Tomamichel and Hayashi, which have the particular advantage of satisfying the data-processing inequality, i.e., monotonicity under quan...
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We introduce two variants of the information spectrum relative entropy defined by Tomamichel and Hayashi, which have the particular advantage of satisfying the data-processing inequality, i.e., monotonicity under quantum operations. This property allows us to obtain one-shot bounds for various information-processing tasks in terms of these quantities. Moreover, these relative entropies have a second-order asymptotic expansion, which in turn yields tight second-order asymptotics for optimal rates of these tasks in the independent and identically distributed setting. The tasks studied in this paper are fixed-length quantum source coding, noisy dense coding, entanglement concentration, pure-state entanglement dilution, and transmission of information through a classical-quantum channel. In the latter case, we retrieve the second-order asymptotics obtained by Tomamichel and Tan. Our results also yield the known second-order asymptotics of fixed-length classical source coding derived by Hayashi. The second-order asymptotics of entanglement concentration and dilution provide a refinement of the inefficiency of these protocols-a quantity which, in the case of entanglement dilution, was studied by Harrow and Lo. We prove how the discrepancy between the optimal rates of these two processes in the second-order implies the irreversibility of entanglement concentration established by Kumagai and Hayashi. In addition, the spectral divergence rates of the information spectrum approach (ISA) can be retrieved from our relative entropies in the asymptotic limit. This enables us to directly obtain the more general results of the ISA from our one-shot bounds.
This paper studies fixed-rate randomized vector quantization under the constraint that the quantizer's output has a given fixed probability distribution. A general representation of randomized quantizers that incl...
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This paper studies fixed-rate randomized vector quantization under the constraint that the quantizer's output has a given fixed probability distribution. A general representation of randomized quantizers that includes the common models in the literature is introduced via appropriate mixtures of joint probability measures on the product of the source and reproduction alphabets. Using this representation and results from optimal transport theory, the existence of an optimal (minimum distortion) randomized quantizer having a given output distribution is shown under various conditions. For sources with densities and the mean square distortion measure, it is shown that this optimum can be attained by randomizing quantizers having convex codecells. For stationary and memoryless source and output distributions, a rate-distortion theorem is proved, providing a single-letter expression for the optimum distortion in the limit of large blocklengths.
The use of multiple-input, multiple-output (MIMO) technology is proposed to provide unequal error protection (UEP) for layered source coding. Two priority layers are considered: a base (high priority (HP)) layer and a...
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The use of multiple-input, multiple-output (MIMO) technology is proposed to provide unequal error protection (UEP) for layered source coding. Two priority layers are considered: a base (high priority (HP)) layer and an enhancement (low priority (LP))...
A modified proof of T. Berger\'s (1971) abstract alphabet source coding with a fidelity criterion theorem is provided, utilizing a variant of a result from large deviation theory. This proof does not use an asympt...
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A modified proof of T. Berger\'s (1971) abstract alphabet source coding with a fidelity criterion theorem is provided, utilizing a variant of a result from large deviation theory. This proof does not use an asymptotic equipartition property of any kind, thus providing what appears to be a more direct approach to this key result.
We consider the lossless compression of binary memoryless sources using a library of turbo codes. The message is compressed by each code and the best result along with the index of the applied code is sent to the deco...
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We consider the lossless compression of binary memoryless sources using a library of turbo codes. The message is compressed by each code and the best result along with the index of the applied code is sent to the decoder. Instead of transmitting the code index, we find a criterion to detect the code index using the transmitted parities. Our method helps to reduce the compression rate of short block length turbo source coders.
In many applications of wireless sensor networks (such as military communications), secure communication, message delay minimization and energy efficiency are crucial. Such requirements constrain special or Important ...
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In many applications of wireless sensor networks (such as military communications), secure communication, message delay minimization and energy efficiency are crucial. Such requirements constrain special or Important Cluster Head (ICH) placement over the network architecture modeled by a tree. The optimal important cluster head placement problem is formulated and solved using source coding results (providing minimum possible delay and security through prefix-free paths over the tree). Also, through simulations energy efficiency of the proposed approach is established. The reported research is naturally applicable for many applications of Wireless Sensor Networks (WSNs) such as Body Area Networks (BANs).
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