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Santosh Kumar Emmadi

Bio: Santosh Kumar Emmadi is an academic researcher from Texas A&M University. The author has contributed to research in topics: Fourier transform & Expander code. The author has an hindex of 2, co-authored 3 publications receiving 32 citations. Previous affiliations of Santosh Kumar Emmadi include Indian Institute of Technology Madras.

Papers
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Proceedings ArticleDOI
29 Oct 2015
TL;DR: Results show that symmetric product codes have a larger normalized minimum distance than the product code from which they are derived, some small constructions achieve the largest minimum distance possible for a linear code, and they can have better performance in both the waterfall region and the error floor when compared to a product code of similar length and rate.
Abstract: Product codes were introduced by Elias in 1954 and generalized by Tanner in 1981. Recently, a number of generalized product codes have been proposed for forward error-correction in high-speed optical communication. In practice, these codes are decoded by iteratively decoding each of the component codes. Symmetric product codes are a subclass of generalized product codes that use symmetry to reduce the block length of a product code while using the same component code. One example of this subclass, dubbed half-product codes, was introduced by Tanner in 1981 and then generalized by Justesen in 2011. In this paper, we discuss some initial results on symmetric product codes. Our results show that: (i) these codes have a larger normalized minimum distance than the product code from which they are derived, (ii) some small constructions achieve the largest minimum distance possible for a linear code, and (iii) they can have better performance in both the waterfall region and the error floor when compared to a product code of similar length and rate.

35 citations

Proceedings ArticleDOI
01 Sep 2015
TL;DR: It is shown that the recently proposed Fast Fourier Aliasing-based Sparse Transform (FFAST) algorithm for computing the Discrete Fourier Transform (DFT) of signals with a sparse DFT is equivalent to iterative hard decision decoding of product codes.
Abstract: We show that the recently proposed Fast Fourier Aliasing-based Sparse Transform (FFAST) algorithm for computing the Discrete Fourier Transform (DFT) [1] of signals with a sparse DFT is equivalent to iterative hard decision decoding of product codes. This connection is used to derive the thresholds for sparse recovery based on a recent analysis by Justensen [2] for computing thresholds for product codes. We first extend Justesen's analysis to d-dimensional product codes and compute thresholds for the FFAST algorithm based on this. Additionally, this connection also allows us to analyze the performance of the FFAST algorithm under a burst sparsity model in addition to the uniformly random sparsity model which was assumed in prior work [1].

4 citations

Proceedings ArticleDOI
14 May 2014
TL;DR: Performance evaluation of some of the important CAC schemes that are proposed in the literature are evaluated using simulations and numerical computation of the theoretical results.
Abstract: Efficient handoff is an important issue in wireless cellular networks in order to provide Quality of Service (QoS) to the users and to support users' mobility. A related important issue in the cellular networks is the call admission control (CAC). The design of the call admission control schemes is especially challenging given the limited resources, and the mobility of users encountered in such networks. The goal of this paper is to do performance evaluation of some of the important CAC schemes that are proposed in the literature using simulations and numerical computation of the theoretical results. The CAC schemes studied include Non-Prioritized Scheme (NPS), Guard Channel Scheme (GCS), Fractional Guard Channel Scheme (FGCS), Guard Channel Scheme with Buffer (GCSB), Two-Level Fractional Guard channel Scheme (TLFGCS), Dynamic Guard Channel Scheme (DGCS) and Adaptive Guard Channel Scheme (AGCS). The performance results obtained from simulation of all these schemes are compared and conclusions are drawn.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: A novel iterative decoding algorithm for PCs which can detect and avoid most miscorrections, and can be used to decode many recently proposed classes of generalized PCs, such as staircase, braided, and half-product codes.
Abstract: Product codes (PCs) protect a 2-D array of bits using short component codes. Assuming transmission over the binary symmetric channel, the decoding is commonly performed by iteratively applying bounded-distance decoding to the component codes. For this coding scheme, undetected errors in the component decoding—also known as miscorrections—significantly degrade the performance. In this paper, we propose a novel iterative decoding algorithm for PCs which can detect and avoid most miscorrections. The algorithm can also be used to decode many recently proposed classes of generalized PCs, such as staircase, braided, and half-product codes. Depending on the component code parameters, our algorithm significantly outperforms the conventional iterative decoding method. As an example, for double-error-correcting Bose–Chaudhuri–Hocquenghem component codes, the net coding gain can be increased by up to 0.4 dB. Moreover, the error floor can be lowered by orders of magnitude, up to the point where the decoder performs virtually identical to a genie-aided decoder that avoids all miscorrections. We also discuss post-processing techniques that can be used to reduce the error floor even further.

59 citations

Journal ArticleDOI
TL;DR: In this article, the authors considered a deterministic construction of generalized product codes (GPCs) and analyzed the asymptotic performance over the binary erasure channel under iterative decoding.
Abstract: Generalized product codes (GPCs) are extensions of product codes (PCs), where code symbols are protected by two component codes but not necessarily arranged in a rectangular array. We consider a deterministic construction of GPCs (as opposed to randomized code ensembles) and analyze the asymptotic performance over the binary erasure channel under iterative decoding. Our code construction encompasses several classes of GPCs previously proposed in the literature, such as irregular PCs, blockwise braided codes, and staircase codes. It is assumed that the component codes can correct a fixed number of erasures and that the length of each component code tends to infinity. We show that this setup is equivalent to studying the behavior of a peeling algorithm applied to a sparse inhomogeneous random graph. Using a convergence result for these graphs, we derive the density evolution equations that characterize the asymptotic decoding performance. As an application, we discuss the design of irregular GPCs, employing a mixture of component codes with different erasure-correcting capabilities.

34 citations

Posted Content
TL;DR: In this paper, the authors considered a deterministic construction of generalized product codes (GPCs) and analyzed the asymptotic performance over the binary erasure channel under iterative decoding.
Abstract: Generalized product codes (GPCs) are extensions of product codes (PCs) where code symbols are protected by two component codes but not necessarily arranged in a rectangular array. We consider a deterministic construction of GPCs (as opposed to randomized code ensembles) and analyze the asymptotic performance over the binary erasure channel under iterative decoding. Our code construction encompasses several classes of GPCs previously proposed in the literature, such as irregular PCs, block-wise braided codes, and staircase codes. It is assumed that the component codes can correct a fixed number of erasures and that the length of each component code tends to infinity. We show that this setup is equivalent to studying the behavior of a peeling algorithm applied to a sparse inhomogeneous random graph. Using a convergence result for these graphs, we derive the density evolution equations that characterize the asymptotic decoding performance. As an application, we discuss the design of irregular GPCs employing a mixture of component codes with different erasure-correcting capabilities.

23 citations

Proceedings ArticleDOI
20 Mar 2016
TL;DR: Deterministically constructed (i.e., non-ensemble-based) codes in the waterfall and error floor region are analyzed to apply to several FEC classes proposed for high-speed OTNs such as staircase and braided codes.
Abstract: We analyze deterministically constructed (i.e., non-ensemble-based) codes in the waterfall and error floor region. The analysis directly applies to several FEC classes proposed for high-speed OTNs such as staircase and braided codes.

13 citations

Journal ArticleDOI
TL;DR: A new family of mappings of EBs into 2-D PBs on magnetic tape is introduced, which fulfills the stringent burst-error-correction requirements of tape storage and demonstrates the improved error-rate performance of 3-D product codes over 2- D product codes.
Abstract: For 2-D product codes used in tape storage, the mapping of error-correction-coding (ECC) blocks (EBs) into 2-D physical blocks (PBs) on magnetic tape is generalized. The 3-D product codes that have the same code rate and EB size as interleaved 2-D product codes currently used in tape storage are proposed. For 3-D product codes, a new family of mappings of EBs into 2-D PBs on magnetic tape is introduced, which fulfills the stringent burst-error-correction requirements of tape storage. The burst-error-correction capability of 2-D and 3-D product code words recorded on magnetic tape is analyzed as a function of track rotation, linear density, and ECC parameters. The performance limits of the tape-storage channel are determined based on computations of channel capacity and random coding bound. Hardware simulations of iterative hard-decision decoding of product codes implemented in a field-programmable gate array demonstrate the improved error-rate performance of 3-D product codes over 2-D product codes.

12 citations