arXiv subjects

Emin Martinian

Publications and source records attributed to Emin Martinian.

12 recordsLinked to original sources

arXiv2011

Diversity Embedded Streaming Erasure Codes (DE-SCo): Constructions and Optimality

Streaming erasure codes guarantee that each source packet is recovered within a fixed delay at the receiver over a burst-erasure channel. This paper introduces a new class of streaming codes: Diversity Embedded Streaming Erasure Codes (DE-SCo), that provide a flexible tradeoff between the channel quality and receiver delay. When the channel conditions are good, the source stream is recovered with a low delay, whereas when the channel conditions are poor the source stream is still recovered, albeit with a larger delay. Information theoretic analysis of the underlying burst-erasure broadcast channel reveals that DE-SCo achieve the minimum possible delay for the weaker user, without sacrificing the single-user optimal performance of the stronger user. Our constructions are explicit, incur polynomial time encoding and decoding complexity and outperform random linear codes over burst-erasure channels.

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arXiv2010

Diversity Embedded Streaming Erasure Codes (DE-SCo): Constructions and Optimality

Streaming erasure codes encode a source stream to guarantee that each source packet is recovered within a fixed delay at the receiver over a burst-erasure channel. This paper introduces diversity embedded streaming erasure codes (DE-SCo), that provide a flexible tradeoff between the channel quality and receiver delay. When the channel conditions are good, the source stream is recovered with a low delay, whereas when the channel conditions are poor the source stream is still recovered, albeit with a larger delay. Information theoretic analysis of the underlying burst-erasure broadcast channel reveals that DE-SCo achieve the minimum possible delay for the weaker user, without sacrificing the performance of the stronger user. A larger class of multicast streaming erasure codes (MU-SCo) that achieve optimal tradeoff between rate, delay and erasure-burst length is also constructed.

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arXiv2007

Low-density graph codes that are optimal for source/channel coding and binning

We describe and analyze the joint source/channel coding properties of a class of sparse graphical codes based on compounding a low-density generator matrix (LDGM) code with a low-density parity check (LDPC) code. Our first pair of theorems establish that there exist codes from this ensemble, with all degrees remaining bounded independently of block length, that are simultaneously optimal as both source and channel codes when encoding and decoding are performed optimally. More precisely, in the context of lossy compression, we prove that finite degree constructions can achieve any pair $(R, D)$ on the rate-distortion curve of the binary symmetric source. In the context of channel coding, we prove that finite degree codes can achieve any pair $(C, p)$ on the capacity-noise curve of the binary symmetric channel. Next, we show that our compound construction has a nested structure that can be exploited to achieve the Wyner-Ziv bound for source coding with side information (SCSI), as well as the Gelfand-Pinsker bound for channel coding with side information (CCSI). Although the current results are based on optimal encoding and decoding, the proposed graphical codes have sparse structure and high girth that renders them well-suited to message-passing and other efficient decoding procedures.

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arXiv2006

Low-density constructions can achieve the Wyner-Ziv and Gelfand-Pinsker bounds

We describe and analyze sparse graphical code constructions for the problems of source coding with decoder side information (the Wyner-Ziv problem), and channel coding with encoder side information (the Gelfand-Pinsker problem). Our approach relies on a combination of low-density parity check (LDPC) codes and low-density generator matrix (LDGM) codes, and produces sparse constructions that are simultaneously good as both source and channel codes. In particular, we prove that under maximum likelihood encoding/decoding, there exist low-density codes (i.e., with finite degrees) from our constructions that can saturate both the Wyner-Ziv and Gelfand-Pinsker bounds.

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arXiv2006

Analysis of LDGM and compound codes for lossy compression and binning

Recent work has suggested that low-density generator matrix (LDGM) codes are likely to be effective for lossy source coding problems. We derive rigorous upper bounds on the effective rate-distortion function of LDGM codes for the binary symmetric source, showing that they quickly approach the rate-distortion function as the degree increases. We also compare and contrast the standard LDGM construction with a compound LDPC/LDGM construction introduced in our previous work, which provably saturates the rate-distortion bound with finite degrees. Moreover, this compound construction can be used to generate nested codes that are simultaneously good as source and channel codes, and are hence well-suited to source/channel coding with side information. The sparse and high-girth graphical structure of our constructions render them well-suited to message-passing encoding.

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arXiv2006

Low density codes achieve the rate-distortion bound

We propose a new construction for low-density source codes with multiple parameters that can be tuned to optimize the performance of the code. In addition, we introduce a set of analysis techniques for deriving upper bounds for the expected distortion of our construction, as well as more general low-density constructions. We show that (with an optimal encoding algorithm) our codes achieve the rate-distortion bound for a binary symmetric source and Hamming distortion. Our methods also provide rigorous upper bounds on the minimum distortion achievable by previously proposed low-density constructions.

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arXiv2005

Authentication with Distortion Criteria

In a variety of applications, there is a need to authenticate content that has experienced legitimate editing in addition to potential tampering attacks. We develop one formulation of this problem based on a strict notion of security, and characterize and interpret the associated information-theoretic performance limits. The results can be viewed as a natural generalization of classical approaches to traditional authentication. Additional insights into the structure of such systems and their behavior are obtained by further specializing the results to Bernoulli and Gaussian cases. The associated systems are shown to be substantially better in terms of performance and/or security than commonly advocated approaches based on data hiding and digital watermarking. Finally, the formulation is extended to obtain efficient layered authentication system constructions.

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arXiv2004

Source-Channel Diversity for Parallel Channels

We consider transmitting a source across a pair of independent, non-ergodic channels with random states (e.g., slow fading channels) so as to minimize the average distortion. The general problem is unsolved. Hence, we focus on comparing two commonly used source and channel encoding systems which correspond to exploiting diversity either at the physical layer through parallel channel coding or at the application layer through multiple description source coding. For on-off channel models, source coding diversity offers better performance. For channels with a continuous range of reception quality, we show the reverse is true. Specifically, we introduce a new figure of merit called the distortion exponent which measures how fast the average distortion decays with SNR. For continuous-state models such as additive white Gaussian noise channels with multiplicative Rayleigh fading, optimal channel coding diversity at the physical layer is more efficient than source coding diversity at the application layer in that the former achieves a better distortion exponent. Finally, we consider a third decoding architecture: multiple description encoding with a joint source-channel decoding. We show that this architecture achieves the same distortion exponent as systems with optimal channel coding diversity for continuous-state channels, and maintains the the advantages of multiple description systems for on-off channels. Thus, the multiple description system with joint decoding achieves the best performance, from among the three architectures considered, on both continuous-state and on-off channels.

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arXiv2004

Source Coding With Encoder Side Information

We introduce the idea of distortion side information, which does not directly depend on the source but instead affects the distortion measure. We show that such distortion side information is not only useful at the encoder, but that under certain conditions, knowing it at only the encoder is as good as knowing it at both encoder and decoder, and knowing it at only the decoder is useless. Thus distortion side information is a natural complement to the signal side information studied by Wyner and Ziv, which depends on the source but does not involve the distortion measure. Furthermore, when both types of side information are present, we characterize the penalty for deviating from the configuration of encoder-only distortion side information and decoder-only signal side information, which in many cases is as good as full side information knowledge.

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arXiv2004

Source Coding with Fixed Lag Side Information

We consider source coding with fixed lag side information at the decoder. We focus on the special case of perfect side information with unit lag corresponding to source coding with feedforward (the dual of channel coding with feedback) introduced by Pradhan. We use this duality to develop a linear complexity algorithm which achieves the rate-distortion bound for any memoryless finite alphabet source and distortion measure.

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arXiv2004

Source Coding With Distortion Side Information At The Encoder

We consider lossy source coding when side information affecting the distortion measure may be available at the encoder, decoder, both, or neither. For example, such distortion side information can model reliabilities for noisy measurements, sensor calibration information, or perceptual effects like masking and sensitivity to context. When the distortion side information is statistically independent of the source, we show that in many cases (e.g, for additive or multiplicative distortion side information) there is no penalty for knowing the side information only at the encoder, and there is no advantage to knowing it at the decoder. Furthermore, for quadratic distortion measures scaled by the distortion side information, we evaluate the penalty for lack of encoder knowledge and show that it can be arbitrarily large. In this scenario, we also sketch transform based quantizers constructions which efficiently exploit encoder side information in the high-resolution limit.

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arXiv2004

Iterative Quantization Using Codes On Graphs

We study codes on graphs combined with an iterative message passing algorithm for quantization. Specifically, we consider the binary erasure quantization (BEQ) problem which is the dual of the binary erasure channel (BEC) coding problem. We show that duals of capacity achieving codes for the BEC yield codes which approach the minimum possible rate for the BEQ. In contrast, low density parity check codes cannot achieve the minimum rate unless their density grows at least logarithmically with block length. Furthermore, we show that duals of efficient iterative decoding algorithms for the BEC yield efficient encoding algorithms for the BEQ. Hence our results suggest that graphical models may yield near optimal codes in source coding as well as in channel coding and that duality plays a key role in such constructions.

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