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EAI Endorsed Transactions on Cognitive Communications: Online First

Issue 0, 2018
Editor(s)-in-Chief: Xin Liu

  • Joint Encoding and Decoding Optimization of LT Codes over Noise Channels

    Appears in:
    cogcom 18: e1

    Authors:
    Mingli Chi, Wenzhu Sun

    Abstract:
    The low-degree variable nodes and high residual errors of Belief Propagation (BP) decoding are key factors of high error floor of LT Codes over noise channels. A joint encoding and decoding scheme are proposed to lower this error floor. The Regularized Variable-Node (RVN) encoding method is adopted…The low-degree variable nodes and high residual errors of Belief Propagation (BP) decoding are key factors of high error floor of LT Codes over noise channels. A joint encoding and decoding scheme are proposed to lower this error floor. The Regularized Variable-Node (RVN) encoding method is adopted to maximize the minimum degree and avoid the lowdegree variable node. By investigating the characteristic of error patterns in error frames and the relationship between error bits and their Log-likelihood Ratio (LLR) values, the most unreliable bits are identified after BP decoding. Thanks to the
    Cyclic Redundancy Check (CRC) detector, the residual error bits of BP decoder are identified and corrected by bit flip. The simulation results demonstrate that the proposed method can dramatically reduce the frame error rate in the error floor region at the cost of almost negligible extra computation.
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  • Software Articles and Open Source Research Software: The Why, the What, and the How

    Appears in:
    cogcom 18: e3

    Author:
    Vincent A. Cicirello

    Abstract:
    In this editorial, I make the case for why you should write and publish software articles about your open source research software. I begin by discussing some of the benefits of releasing your research software as an open source project. Then, I explain what a software article is in general, as wel…In this editorial, I make the case for why you should write and publish software articles about your open source research software. I begin by discussing some of the benefits of releasing your research software as an open source project. Then, I explain what a software article is in general, as well as why you should consider writing one about your research software, such as increased reproducibility, increased software reuse, the potential to increase the impact that your research has on the work of others, the potential to gain new collaborators, among other advantages. Open source enables these things, and software articles enhance the process by increasing discoverability, as well as by placing the software within a broader research context. I then discuss how to proceed to write a software article more specifically for submission to the EAI Transactions on Cognitive Communications, using either the “research article” or “short communications” article types.
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  • Comparative Analysis of Scene Classification Methods for Remotely Sensed Images using Various Convolutional Neural Network

    Appears in:
    cogcom 18: e4

    Authors:
    P. Deepan, L.R. Sudha

    Abstract:
    Remote sensing image (RSI) scene classification has received growing attention from the research community in recent days. Over the past few decades, with the rapid development of deep learning models particularly Convolutional Neural Network (CNN), the performance …Remote sensing image (RSI) scene classification has received growing attention from the research community in recent days. Over the past few decades, with the rapid development of deep learning models particularly Convolutional Neural Network (CNN), the performance of RSI scene classifications has been drastically improved due to the hierarchical feature representation learning through traditional CNN. But, we found that these models suffer from characterizing complex patterns in remote sensing imagery because of small inter class variations and large intra class variations. In order to tackle these problems, we have finetuned and proposed three different CNN models namely, Dilated CNN (D-CNN), RSI Scene Classification model (RSISC-16 Net) and fused the features of CNN and RSISC-16Net to improve the performance of RSI scene classification. The aim of proposed CNN models is to incorporate more relevant information by increasing the receptive field of convolutional layer. In addition, we have performed feature fusion of two CNN models and finetuned by varying hyper parameters such as activation function, dropout probability and batch size to reduce over fitting problem and to improve the performance of our proposed work. For evaluating the proposed approach, we have collected 7,000 remote sensing images from NWPU 45-class dataset and the experiments are carried out using different CNN models and results. The obtained accuracy is 89.85%, 94.7% and 96.5% respectively.
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Scope

The application of intelligent technologies in communication systems could be tracked back into 1990s. The emerging of cognitive radio targeted on the revolutionary spectrum access paradigm has sparked a radical change on wireless system design, development and performance analysis.

Since then …

The application of intelligent technologies in communication systems could be tracked back into 1990s. The emerging of cognitive radio targeted on the revolutionary spectrum access paradigm has sparked a radical change on wireless system design, development and performance analysis.

Since then the state-of-the art of wireless communications has been significantly advanced, from substantial improvement on spectrum usage, smart adaptation and coexistence in radio and network environments, fundamental enhancement on performance and capacity, to considerable reduction of complexity in network management. After a decade of research on cognitive radio and networks, the concept of cognition has been naturally and widely extended to whole communication areas, not limited to wireless systems, but also in wired networks.

Cognitive technologies become promising tools for the communication industry to meet the challenge of coming data traffic tsunami. Solutions for energy efficient, sustainable future Internet are heavily relied on advanced cognitive technologies, new ways of thinking on network design and development, as well as new theoretic foundations. We believe cognitive communication technologies will remain an important and active area of research for next several decades.

It becomes necessary to provide a common forum to publish high quality papers, and to offer readers a single source to get inspiring ideas and important findings in this area. It is our honor to create, for the first time, dedicated transactions on cognitive technologies for communications, to fulfill this purpose.

The aims of the transactions are:

  • to provide a dedicated platform for timely publishing of high quality, peer-reviewed, original papers in fields of cognitive communications;
  • to become a highly cited source of latest findings in cognitive radio and cognitive communication networks;
  • to become a leading journal that advances the state-of-the art of communications from a well-focused direction.

The transactions provide flexible means to publish latest results in a timely manner. It accepts the submission of:

  • regular research papers, for original scientific contributions,
  • fast-track communications, for short findings,
  • topical reviews.
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Topics

The scope of the transactions includes, but not limited to:

  • Information-theoretic aspects of cognitive communication systems
  • Spectrum sensing and dynamic spectrum access
  • Spectrum pricing, economics models and game-theoretical strategies
  • Interference analysis and statistical mode…

The scope of the transactions includes, but not limited to:

  • Information-theoretic aspects of cognitive communication systems
  • Spectrum sensing and dynamic spectrum access
  • Spectrum pricing, economics models and game-theoretical strategies
  • Interference analysis and statistical models of spectrum usage
  • Physical (PHY) layer design for cognitive radios
  • Dynamic medium access control techniques for cognitive communication systems
  • Dynamic resource allocation in cognitive communication systems
  • Co-existence of heterogeneous networks
  • Artificial intelligence and machine learning for cognitive communication systems
  • Context-aware, emotion-aware, as well as personalized cognitive communication systems
  • (Big) data analytics for cognitive communication systems
  • Cognitive communication systems for the Internet of Things (IoT)
  • Bio-inspired communication systems
  • Cooperative techniques in cognitive communication systems
  • Cross-layer optimization for cognitive communication systems
  • Routing and network technologies for cognitive communication systems
  • Trust, security, and privacy issues in cognitive communication systems
  • Energy-efficiency design in cognitive communication systems
  • Software defined radio
  • Self-organizing, self-aware, and self-adaptive networks
  • Applications enabled by cognitive communication systems
  • Open source for cognitive communications
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Indexing

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Editorial Board

  • Antti Anttonen (VTT, Finland)
  • Aawatif Hayar (University Hassan II Casablanca, Morocco)
  • Abdur Rahim Biswas (Create-Net, Italy)
  • Bo Li (Harbin Institute of Technology at Weihai)
  • Fei Wang (Nanjing University of Aeronautics and Astronautics)
  • Hong Jiang (South West University…
  • Antti Anttonen (VTT, Finland)
  • Aawatif Hayar (University Hassan II Casablanca, Morocco)
  • Abdur Rahim Biswas (Create-Net, Italy)
  • Bo Li (Harbin Institute of Technology at Weihai)
  • Fei Wang (Nanjing University of Aeronautics and Astronautics)
  • Hong Jiang (South West University of Science and Technology)
  • Javier Del Ser (Tecnalia and University of the Basque Country)
  • Javier Jel Ser (TECNALIA Research & Innovation, Spain)
  • Jianhua Zhang (Beijing University of Posts and Telecommunications, China)
  • Lijun Qian (Prairie View A&M University, USA)
  • Marcos Katz (University of Oulu, Finland)
  • Mikko Valkama (Tampere University of Technology, Finland)
  • Pinyi Ren (Xi’an Jiaotong University, China)
  • Tao Han (Huazhong University of Science and Technology)
  • Wei Cheng (The George Washington University, USA)
  • Weidang Lu (Zhejiang University of Technology)
  • Xianfu Chen (VTT, Finland)
  • Xiang Chen (Tsinghua University, China)
  • Xiangping Zhai (Nanjing University of Aeronautics and Astronautics)
  • Xiaolong Yang (Chongqing University of Posts and Telecommunications)
  • Xuanheng Li (Dalian University of Technology)
  • Xueyan Zhang (Dalian University of Technology)
  • Yan Zhang (Simula Research Laboratory, Norway)
  • Yong Wang (Chongqing University of Posts and Telecommunications)
  • Zheng Chang (University of Jyväskylä)
  • Zhengquan Li (School of Iot Engineering, Jiangnan.University)
  • Zhenyu Na (School of Information Science and Technology, Dalian Maritime University)
  • Zhiwei Mao (Fairleigh Dickinson University, USA)
  • Murat Kuscu (Koc University, Turkey)
  • Pandelis Kourtessis (University of Hertfordshire, UK)
  • Klaus Moessner (University of Surrey, UK)
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Journal Blurb

<p>This journal is closed, meaning new submissions are not being considered. We have merged the journal with <a title="EAI Endorsed Transactions on Mobile Communications and Applications" href="http://eudl.eu/journal/mca">EAI Endorsed Transactions on Mobile Communications and Applications</a>, thus…

<p>This journal is closed, meaning new submissions are not being considered. We have merged the journal with <a title="EAI Endorsed Transactions on Mobile Communications and Applications" href="http://eudl.eu/journal/mca">EAI Endorsed Transactions on Mobile Communications and Applications</a>, thus, please send your article to this title.</p>

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Publisher
EAI
ISSN
2313-4534
Volume
0
Published
2018-07-13