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distributed Soft coding with a Soft Input Soft Output (SISO) Relay Encoder in Parallel Relay Channels

IEEE TRANSACTIONS ON COMMUNICATIONS 2013年第9期61卷 3660-3672页

作者： Li, Yonghui Rahman, Md. Shahriar Ng, Soon Xin Vucetic, Branka Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

In this paper, we propose a new distributed coding structure with a soft input soft output (SISO) relay encoder for error-prone parallel relay channels. We refer to it as the distributed soft coding (DISC). In the proposed scheme, each relay first uses the received noisy signals to calculate the soft bit estimate (SBE) of the source symbols. A simple SISO encoder is developed to encode the SBEs of source symbols based on a constituent code generator matrix. The SISO encoder outputs at different relays are then forwarded to the destination and form a distributed codeword. The performance of the proposed scheme is analyzed. It is shown that its performance is determined by the generator sequence weight (GSW) of the relay constituent codes, where the GSW of a constituent code is defined as the number of ones in its generator sequence. A new coding design criterion for optimally assigning the constituent codes to all the relays is proposed based on the analysis. Results show that the proposed DISC can effectively circumvent the error propagation due to the decoding errors in the conventional detect and forward (DF) with relay re-encoding and bring considerable coding gains, compared to the conventional soft information relaying.

关键词： Cooperative communications Decode and Forward distributed coding Relay Networks Soft coding

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Optimization of a Modular Ad Hoc Land Wireless System via distributed Joint Source-Network coding for Correlated Sensors 16th

Optimization of a Modular Ad Hoc Land Wireless System via Di...

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16th International Conference on Ad-Hoc Networks and Wireless (ADHOC-NOW)

作者： Chaal, Dina Chahboun, Asaad Lehmann, Frederic Lyhyaoui, Abdelouahid ENSA Tangier LTI Lab Tangier Morocco Telecom SudParis SAMOVAR Lab Evry France

ISBN: (纸本)9783319679105;9783319679099

This paper outlines a proposition of a framework optimizing the communication scheme from the physical part of the transmitters to the data gathered at the receiver in a wireless sensor network. We propose a coding scheme able to take into account the correlation between measurements obtained by the sensors. This scheme consists of joint distributed source encoding and linear network coding. Several coding strategies are compared. (1) linear source coding, based on the low density generator matrix (LDGM) codes, where the compression process is performed by every sensor independently (2) distributed source coding, where the correlation between sources is taken into account, without cooperation between sensors. The compression ratios costs are evaluated analytically for each strategy, with respect to the communication costs between the nodes of the network. The results show a significant improvement in terms of compression rate and distortion compared to linear source encoding.

关键词： Wireless Sensor Networks Modular Ad-hoc networks Lossless compression Source and network coding distributed coding Random Linear Network coding (RLNC)

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Edge Learning based Green Content Distribution for Information-Centric Internet of Things 42

Edge Learning based Green Content Distribution for Informati...

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42nd International Conference on Telecommunications and Signal Processing (TSP)

作者： Shen, Qili Wu, Jun Li, Jianhua Shanghai Jiao Tong Univ Sch Cyber Secur Shanghai Peoples R China

ISBN: (纸本)9781728118642

Being the revolutionary future networking architecture, information-centric networking (ICN) conducts network distribution based on content, which is ideally suitable for Internet of things (IoT). With the rapid growth of network traffic, compared to the conventional IoT, information-centric Internet of things (IC-IoT) is expected to provide users with the better satisfaction of the network quality of service (QoS). However, due to IC-IoT requirements of low latency, large data volume, marginalization, and intelligent processing, it urgently needs an efficient content distribution system. In this paper, we propose an edge learning based green content distribution scheme for IC-IoT. We implement intelligent path selection based on decision tree and edge calculation. Moreover, we apply distributed coding based content transmission to enhance the speed and recovery capability of content. Meanwhile, we have verified the effectiveness and performance of this scheme based on a large number of simulation experiments. The work of this paper is of great significance to improve the efficiency and flexibility of content distribution in IC-IoT.

关键词： content distribution distributed coding edge learning IC-IoT intelligent

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You Can Observe a Lot by Watching: Hughlings Jackson's Underappreciated and Prescient Ideas about Brain Control of Movement

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NEUROSCIENTIST 2018年第5期24卷 448-455页

作者： Berkowitz, Ari Univ Oklahoma Dept Biol 730 Van Vleet Oval Norman OK 73019 USA

John Hughlings Jackson, the 19th-century British neurologist, first described what are today called Jacksonian seizures. He is generally associated with somatotopy, the idea that neighboring brain regions control neighboring body parts, as later represented pictorially in Wilder Penfield's "homunculus", or little man in the brain. Jackson's own views, however, were quite different, though this is seldom appreciated. In an 1870 article, Jackson advanced the hypotheses that each region of the cerebrum controls movements of multiple body parts, but to different degrees, and that the march of movements that typically occurs during Jacksonian seizures is caused by the downstream connections of the overactive neurons at the seizure focus, rather than a somatotopic organization of the cerebrum. Jackson's hypotheses, which were based almost entirely on his careful observations of movements during seizures, are well within the range of current hypotheses about how the frontal lobe is organized to control movements and thus deserve renewed attention.

关键词： Hughlings Jackson motor cortex somatotopy homunculus distributed coding

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A Noise-Invariant Sparse coding Model for Binary Input

A Noise-Invariant Sparse Coding Model for Binary Input

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International Conference on Intelligent Computing, Automation and Systems (ICICAS)

作者： Tao Zhou Yuanyuan Chen University of Electronic Science and Technology of China UESTC Chengdu China Sichuan University SCU Chengdu China

ISBN: (数字)9781728161068

ISBN: (纸本)9781728161075

A sparse distributed coding model that is consistent with the basic properties of the primary visual cortex is introduced. The binary input can be sparsely represented after a learning stage. The results of the sparse distributed coding have only a few nonzero coefficients to represent the input. In addition, it can also get the relative noise-robust representation. Firstly, a set of basic binary images or basic vectors can be found from the training data. Secondly, any binary input with the same dimension can be described as a linear combination of the basic vectors. According to the experimental results, the proposed coding model not only.

关键词： image coding image representation learning (artificial intelligence) vectors image representation image coding binary input distributed coding Cloning Vectors Striate Cortex Linear Combination Sparse coding Alkali Basic language

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distributed Rateless coding with Cooperative Sources

Distributed Rateless Coding with Cooperative Sources

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IEEE International Symposium on Information Theory

作者： Shirvanimoghaddam, Mahyar Li, Yonghui Vucetic, Branka Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia

ISBN: (纸本)9781467325790

In this paper, we propose a distributed rateless coding (DRC) scheme for a two-user cooperative system. In DRC, the overall transmission is divided into two phases, a broadcast phase and a cooperation phase. In the broadcast phase, each user keeps transmitting its rateless coded symbols to the other user and the destination until its message has been successfully decoded by the destination or the other user. In the cooperation phase, each user encodes both users' messages by using a rateless code and transmits them to the destination. A linear programming optimization problem is then formulated to find the optimal degree distribution for the proposed distributed rateless code. The performance of the proposed code is analyzed and validated by simulations.

关键词： distributed coding rateless code LT coding erasure channel

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Performance analysis of coding using distributed Turbo Codes 3

Performance analysis of coding using Distributed Turbo Codes

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3rd International Workshop on RFID and Adaptive Wireless Sensor Networks (RAWSN)

作者： Aboudeine, Anas Ayoub, Fouad Yatribi, Anouar Benattou, Mohammed Ibn Tofal Univ LRIT Lab Fac Sci Kenitra Morocco CRMEF Kenitra Morocco Mohammed V Univ SIME Lab TSE Team ENSIAS Rabat Morocco

ISBN: (纸本)9781467380966

Nowadays the need for fast and reliable communication is increasing, which leads us to look for new ways to enhance channel coding. In this paper, we will study the case of a distributed coding between two users that aim to transmit data to a common destination, where each user transmits a partial redundancy to the destination, and relies on the second user for the remaining. The purpose of distributing the redundancy creation and transmission, is to benefit from each user channel quality for a more accurate decoding. In the context of our analysis, we will use a 1/2 rate convolutional code with between users and a distributed Turbo code for transmission to the destination. However, this study will aim to highlight the different key factors, as well as the advantage of choosing a distributed encoding.

关键词： turbo codes distributed coding destination Consumers Distribute Channel coding key factors redundancy coding convolutional coding

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A CLASSIFIER-BASED DEcoding APPROACH FOR LARGE SCALE distributed coding

A CLASSIFIER-BASED DECODING APPROACH FOR LARGE SCALE DISTRIB...

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Viswanatha, Kumar Ramaswamy, Sharadh Saxena, Ankur Rose, Kenneth Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)9781457705397

Canonical distributed quantization schemes do not scale to large sensor networks due to the exponential decoder storage complexity that they entail. Prior efforts to tackle this issue have largely been limited to the suboptimal schemes of source grouping and decoding, thus failing to use all available information at the decoder. We propose a new decoding paradigm where all received bits are used in decoding. Essentially, to decode each source, we partition the space of received bit-tuples using a nearest neighbor quantizer at a decoding rate consistent with the allowed complexity and each partition is then mapped to a reconstruction value for that source. To avoid local minima in design, we resort to deterministic annealing to determine the nearest neighbor partition function (the partitioning prototypes) from the training set. Results on several data-sets show substantial gains over naive and other competing approaches.

关键词： distributed coding large scale sensor networks data compression quantization codebook complexity

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New Soft-Encoding Relay (SoER) Mechanisms for Wireless Relay Systems: Convolutional and Turbo Constructions

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2016年第4期15卷 2443-2457页

作者： Lu, Xuanxuan Li, Jing Liu, Yang Lehigh Univ Dept Elect & Comp Engn Bethlehem PA 18015 USA

A two-hop parallel-relay network is considered in this paper. Conventional schemes investigating the coding strategies at the relay(s) have largely focused on hard encoding, with the exception of one pioneering strategy that proposed a soft distributed encoding using the soft estimate (tanh-based) information. To fully harness the gain promised by soft encoding, this paper focuses on distributed soft encoding strategies at the relays. Unlike the previous work that favors the tanh form for soft encoding, we advocate the range-limited log-likelihood ratios (rLLR) as a better way for the relays to capture the reliability of the messages sent by the sender, and especially to further soft-encode these messages. Based on this, we develop a simple but effective soft-encoding relay (SoER) strategy that exploits the useful features of rLLR. Specifically, the close resemblance of rLLR to the tanh form allows us to derive a very simple convolutional encoding, and the piece-wise linearity of rLLR allows us to evaluate the codeword probability density function (PDF) analytically, which further allows us to derive a Viterbi decoding algorithm using a more precise PDF (in addition to the Gaussian-approximated Viterbi algorithm). We finally extend the nonrecursive convolutional SoER strategy to the turbo SoER strategy. Simulation results confirm the efficiency of the new proposed SoER schemes.

关键词： Cooperative communications distributed coding soft information maximum likelihood estimation

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Non-iterative Content-Adaptive distributed Encoding Through ML Techniques

Non-iterative Content-Adaptive Distributed Encoding Through ...

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SMPTE Technical Conference

作者： Sriram Sethuraman Nithya V. S. Venkata Narayanababu Laveti D Ittiam Systems Pvt. Ltd. Bangalore India

ISBN: (纸本)9781510851771

distributed encoding is desired in content preparation workflows in the cloud to reduce turnaround times. Content-adaptive bit allocation at title, chunk, and even frame level, as opposed to using a fixed ladder of content-independent bit-rates and resolutions, have been proposed to achieve efficiencies in storage and delivery. Many of these methods tend to be iterative in nature and consume significant additional compute resources over 2-pass Variable bit-rate (VBR) encoders. With live use-cases attempting to use a set of distributed encoders to achieve higher bit-rate savings (both through use of higher compression presets and through content-adaptive bit allocation) and consistent quality, there is a need to limit the increase in computational complexity. In this paper, we propose a non-iterative codec-agnostic approach that employs machine learning techniques to perform consistent quality content-adaptive encoding within the constraints of a maximum bit-rate in a manner that makes it equally suitable for live and on-demand workflows. The method has the ability to take a target subjective rating level and allocate appropriate bits for each group of frames to achieve that. The proposed approach also anticipates automatic selection of the right resolution and frame-rate for a given representation within an ABR set, and content-specific encoding parameters to maximize the bit savings and/or visual quality. Test results are presented over a wide range of content types comparing the performance of the proposed approach against 2-pass VBR methods. Initial results indicate that the proposed approach can recover ~85% of the bit-savings possible with exhaustive techniques. The computational complexity of the proposed approach is only 15-20% of 2-pass VBR encoding.

关键词： Bit rate distributed coding variable Bit rate automatic selection complexity classes ENCODER Workflow Iterative

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