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This journal is closed, meaning new submissions are not being considered. We have merged the journal with EAI Endorsed Transactions on Mobile Communications and Applications, thus, please send your article to this title.

Editor(s)-in-Chief: Vincent A. Cicirello and Arianna D'Ulizia

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. This trend will strengthen even more with the advent of fifth-generation (5G) communication networks that will impose new challenges, related mainly to the heterogeneity of such networks, the improvement of the quality of experience of users, and the efficient and sustainable use of network resources. 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. Communication ecosystems need to be equipped with advanced intelligence coming from machine learning, data analytics, and cognitive computing to meet the aforementioned challenges. We believe cognitive communication technologies will remain an important and active area of research for the 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 provide 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 be a highly cited source of latest findings in cognitive radio and cognitive communication networks; and
  • to be a leading journal that publish contributions from a wide range of cross-disciplinary and collaborative domain knowledge related to cognitive technologies for communications, such as cognitive science, information science, computer science, mathematics, physics, and statistics.

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.

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
  • 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)

Vincent A. Cicirello1

Vincent A. Cicirello, Ph.D. is a Professor of Computer Science at Stockton University in Galloway, NJ, USA, where he has been a faculty member since 2005. He is also among the founding faculty of Stockton University's Behavioral Neuroscience program, an interdisciplinary undergraduate minor. He earned a Ph.D. in Robotics from Carnegie Mellon University in 2003, and also graduated from Drexel University in 1999 with an M.S./B.S. in Computer Science, and a B.S. in Mathematics. His research interests include artificial intelligence, computational intelligence, evolutionary computation, machine learning, and swarm intelligence. He was designated an ACM Senior Member in 2011, received the 2005 AAAI Outstanding Paper award, and was nominated for the 2006 GECCO Best Genetic Algorithm Track Paper award. He received a U.S. Patent in 2010, and has published over 50 journal and conference publications. He is a member of AAAI (Life member), ACM (Senior Member), ACM SIGCSE, ACM SIGAI, ACM SIGEVO, CCSC, IEEE, IEEE Computer Society, IEEE Computational Intelligence Society, and SIAM.

Arianna D'Ulizia2

Arianna D’Ulizia graduated in Computer Science Engineering from the “La Sapienza” University in Rome in 2005 and obtained a PhD in Computer Science and Automation from the “Roma Tre” University in Rome in 2009. She is currently a researcher with the Italian National Research Council Institute of Research on Population and Social Policies, Rome.

She is author of more than 70 papers in international journals, conferences and books. She is mainly interested in human-computer interaction, multimodal interaction, visual languages, geographical query languages, social computing, risk governance, knowledge management and innovation.

From 2006 to 2018, she was programme chair for several international workshops and conferences, such as the Workshop on Mobile and Networking Technologies for Social Applications (MONET 2006, MONET 2007, MONET 2008, MONET 2009, MONET 2010, MONET 2011), the Workshop on SOcial and MObile COmputing for Collaborative Environments (SOMOCO 2012, SOMOCO 2013), the Workshop on Mobile and Social Computing for Collaborative Interactions (MSC 2014, MSC 2015), and the International Conference on Responsible Research and Innovation in Science, Innovation and Society (RRI-SIS 2017, RRI-ICT 2018).

She is associate editor of the IEEE Access Journal. She is involved in the editorial board of several international journals in the field of computer science, such as the Journal of Universal Computer Science (J.UCS), the International Journal of Applied Logistics (IJAL) and the International Journal of Mobile Computing and Multimedia Communications (IJMCMC), the EAI Endorsed Transactions on Scalable Information Systems.

She is also a reviewer for several international journals, such as Multimedia Tools And Applications (MTAP), PLoS One, Control & Cybernetics, Sensors, Applied sciences, IEEE Access, International Journal of Innovation and Regional Development, IEEE Transactions on Human-Machine Systems, Advanced Robotics, etc.

She has been a guest editor for several special issues of various international journals, such as the Journal of Computing Science and Engineering, Journal of Next Generation Information Technology, Multimedia Tools and Applications, and ISPRS International Journal of geo-information.

Since 2016, she has been a scientific reviewer for several PRIN, FCS-H2020 PON and Italian “Rita Levi Montalcini” young researchers’ projects. She is part of many programme committees for national and international conferences and workshops.

From 2005 to date, she has participated in 19 European and national projects.


1: Stockton University, USA
2: Consiglio Nazionale delle Ricerche (CNR), Italy

  • Natural Disasters and Agrarian Conflict

    Appears in:
    cogcom 19(14): e4

    Authors:
    Afrizal Afrizal, Adha Fathiah, Jendrius Jendrius

    Published:
    14th Jan 2019

    Abstract:
    The tsunami disaster that stroked Aceh in 2004 not only resulted in massive casualties and huge economic losses, has also resulted in massive horizontal agrarian conflicts. This article will discuss how the natural disaster causes symmetrical agrarian conflicts among inhabitants of neighborhoods. The question to be answered is how did the tsunami cause the agrarian conflicts among the people? How did such agrarian conflicts affect the reconstruction effort of after tsunami which is a series of disaster mitigation. This article uses a literature review consisting of research reports, scientific journal articles, and media reports on the impact of the 2004 Aceh tsunami. Study results suggest that the tsunami disaster resulted in the loss of boundaries of residents-controlled lands and this caused land disputes among neighbors that influences reconstruction efforts undertaken by governments and NGOs. However, local wisdom on conflict mitigation contributes to the settlement of land conflicts and this has contributed to post-tsunami reconstruction efforts in Aceh. With that this article contributes to the development of knowledge on disaster mitigation.

  • Spectral Efficiency of Energy Harvesting Random Cognitive Radio Networks in Dual-slope Model

    Appears in:
    cogcom 19(14): e5

    Authors:
    Rakiba Rayhana, Saifur Rahman Sabuj, Aldrin Nippon Bobby

    Published:
    14th Jan 2019

    Abstract:
    This research article evaluates the performance of an energy harvesting random cognitive radio network employing a dual-slope path-loss model in terms of spectral efficiency. It derives the mathematical expression of spectral efficiency by means of stochastic geometry for secondary receivers present in the network in active mode. The numerical result highlights a rise in the efficiency by 20.7% for an increase of 1 dBm in transmit power at a power splitting ratio of 0.5.

  • HCR-MAC: A High-capacity Receiver-based MAC Protocol for Cognitive Radio Enabled AMI Networks in Smart Grid

    Appears in:
    cogcom 18(14): e3

    Authors:
    Xiao Zhang, Zhichao Qu, Zhuoran Cai

    Published:
    19th Jul 2018

    Abstract:
    The Cognitive Radio (CR) Advanced Metering Infrastructure (AMI) network is considered as a viable solution to enhance various aspects of electric power grid and realize smart grid. However, several challenges are generated due to the harsh wireless environment in smart grid. As a result, throughput and reliability become critical issues. In this regard, we propose HCR-MAC, which is a high-capacity receiver-based MAC protocol for cognitive AMI. HCR-MAC uses a capacity-based auction mechanism and preamble sampling techniques for providing high capacity and reliability. In addition, HCR-MAC explicitly accounts for the peculiarities of a CR environment. Simulation results demonstrate the effectiveness of the proposed protocol as a viable solution for cognitive AMI networks in smart grid.

  • WIFI/PDR indoor integrated positioning system in a multi-floor environment

    Appears in:
    cogcom 18(14): e2

    Authors:
    Maxim Dolgov, Mu Zhou, Yanmeng Wang, Yiyao Liu

    Published:
    18th Jul 2018

    Abstract:
    To improve the accuracy of indoor positioning for location-based services, we created an improved WiFi/PDR integrated positioning and navigation system where we are using Extended Kalman filter (EKF). The proposed algorithm first relies on MEMS in our mobile phone to estimate the velocity and heading angles of the target. Second, the velocity and heading angles, together with the results of WiFi fingerprinting-based positioning, are considered as the input of the EKF for the sake of conducting two-dimensional positioning. Third, the proposed algorithm calculates the altitude of the target by using the real-time recorded barometer. The results of our experiments show that integrated navigation system using Extended Kalman filter can effectively eliminate the accumulated errors in the PDR positioning algorithm and can reduce the influence of the large-scale jump of the WiFi fingerprint positioning result brought by the RSSI disturbance on the positioning accuracy of the system.

  • Research on Intelligent anti-jamming communication with Cognitive Radio

    Appears in:
    cogcom 18(14): e1

    Authors:
    Jingning Wang, Yi Zhang, Meng Liu

    Published:
    18th Jul 2018

    Abstract:
    In order to solve the interfere problem in complex electromagnetic environment, NC-OFDM and TDCS are efficient transmit wave form proposed for cognitive radio. The spectral efficiency and the applicable environment of TDCS are different from NC-OFDM. The simulation results show that NC-OFDM can obtain the higher spectral efficiency and the required SINR is higher, and TDCS can work well in lower SINR environment with different spreading factor. When there is little spectrum hole, spread spectrum is a better choice. There is no threshold of some parameter which can make decision. An artificial intelligence algorithm is proposed to select the optimal one from several wave forms. The input parameters of the algorithm include SINR, interference bandwidth, spectrum holes, etc.

  • Dual-feature spectrum sensing exploiting eigenvalue and eigenvector of the sampled covariance matrix

    Appears in:
    cogcom 18(13): e1

    Authors:
    Yanping Chen, Yulong Gao

    Published:
    11th May 2018

    Abstract:
    The signal can be charactered by both eigenvalues and eigenvectors of covariance matrix. However, the existing detection methods only exploit the eigenvalue or eigenvector. In this paper, we utilize the both eigenvalues and eigenvectors of the sampled covariance matrix to perform spectrum sensing for improving the detection performance. The features of eigenvalues and eigenvectors are considered integratedly and the relationship between the false-alarm probability and the decision threshold is o ered. To testify this method, some simulations are carried out. The results demonstrate that the method shows some advantages in the detection performance over the conventional method only adapting eigenvalues or eigenvectors.

  • The Influence of Noise Uncertainty and SNR Wall on the Performance of Hybrid Sensing Method

    Appears in:
    cogcom 17(12): e2

    Authors:
    M. Kustra, M. Suchanski, K. Kosmowski

    Published:
    14th Dec 2017

    Abstract:
    The paper discusses the hybrid sensing method and presents the hybrid detector (HD) which improves the sensing performance. The proposed HD takes advantage of the energy detection (ED) and a method based on the Covariance Absolute Value (CAV) or Cyclic Autocorrelation Function (CAF). The paper characterizes the limitations of the use of ED resulting from the uncertainty of spectral density of noise power estimation known as ‘SNR Wall’. The paper describes the system model and presents the simulation results for OFDM signal (Orthogonal Frequency Division Multiplexing) of WiMAX system. The simulation results refer to the ideal case of an environment with well-known parameters and for an environment with the uncertainty of spectral density of noise power estimation, as it has been considered in the literature so far.

  • A novel spectrum allocation scheme in femtocell networks using improved graph theory

    Appears in:
    cogcom 17(12): e3

    Authors:
    Lili Yang, Feng Li

    Published:
    13rd Dec 2017

    Abstract:
    In  this  paper,  we  propose  a  novel  spectrum  allocation  scheme  by  using  graph  coloring  and  taking  QoS  thresholds  into  account. The goal of our proposed method is to reduce interference among femtocells deployed densely and improve spectral  efficiency  after  reaching  user’s  QoS  threshold.  We  design  an  interference-based  graph  model  by  detecting  terminals’ transmit power between femtocell stations and classifying the interference levels according to the coloring algorithm. Spectrum resource is allocated based on the QoS requirement of each user in a centralized way. Unlike other spectrum allocation  method  using  graph theory,  we  take  many  significant factors into account in this  paper in  order  to  attain a more practical spectrum optimization solution. The simulation results show that when the scheme is deployed in femtocells  with  high  density,  it  can  effectively  reduce  the  interference  within  same  layer  and  improve  system  capacity  along with spectrum efficiency.

  • Reconfigurable Microstrip Printed Patch Antenna for Future Cognitive Radio Applications

    Appears in:
    cogcom 17(12): e1

    Authors:
    Jonathan Rodriguez, Mina Al-Rawi, I. T. E. Elfergani, Raed Abd-Alhameed, Ifiok Otung, Abubakar Sadiq Hussaini, Widad A. Mshwat, Abdelgader M. Abdalla

    Published:
    13rd Dec 2017

    Abstract:
    A family of compact microstrip antennas are presented targeting applications such as Long-Term Evolution (LTE), Wireless Local Area Networks (WLAN), Universal Mobile Telecommunications system (UMTS), Global System Mobile (GSM) and global positioning system (GPS). These antennas consist of a rectangular shaped structure printed over FR4 substrate. The antenna occupies a small volume of 70x54x1.6mm3. A 50-Ohm strip line was used to feed the proposed antennas. For miniaturization purposes, an I- shaped slot was inserted in the appropriate location on the radiator resulting in the second version (antenna with I-shaped slot). The integration of the slot helped towards shifting the resonant frequency downwards, which potentially created an additional resonant frequency to cover the WLAN2400MHz, but this resonant frequency is still static in nature. Thus, tuning mechanisms were introduced to tune the resonant frequency over a wide continuous frequency range. A lumped capacitor was firstly used as the tuning approach, in which its capacitance was varied from 0.5pF to 3pF, covering the frequency range from 2300MHz to 1500MHz. Secondly, the varactor diode was exploited to verify this; by changing the bias voltage across the varactor from 0.21V to 12.9V, the antenna operates over the targeted range from 1500MHz to 2300MHz. Both the simulated and measured results show a stable performance. The proposed antenna may be suitable for future cognitive radio system.

  • Modeling of Time and Frequency Random Access Network and Throughput Capacity Analysis

    Appears in:
    cogcom 17(11): e3

    Authors:
    Yves Louet, Christophe Moy, Apostolos Kountouris, Vincent Savaux

    Published:
    31st May 2017

    Abstract:
    In this paper, we model the random multi-user multi-channel access network by using the occupancy problem from probability theory, and we combine this with a network interference model in order to derive the achievable throughput capacity of such networks. Furthermore, we compare the randommulti-channel access with a cognitive radio systemin which the users are able to minimize the channels occupancy. Besides, we show that the sampling rate can be reduced under the Nyquist rate if the use of the spectrum resource is known at the gateway side. This scenario is referred as "cognitive radio" context. The mathematical developments and results are illustrated through various simulations results. The proposed model is particularly relevant in analyzing the performance of networks where the users are not synchronized neither in time nor in frequency as it is often the case in various Internet of Things (IoT) applications.

  • Energy-Based Cooperative Spectrum Sensing of SC-FDMA Systems

    Appears in:
    cogcom 14(1): e2

    Authors:
    Lie-Liang Yang, Fucheng Yang

    Downloads:
    3935

    Abstract:
    In this paper, we propose a frequency-hopping M-ary frequency-shift keying spectrum sensing network (FH/MFSK SSN) for identifying the on/off states of the users supported by a single-carrier frequency-division multiple assess (SC-FDMA) primary radio (PR) system. Specifically, the spectrums of an uplink interleaved frequency-division multiple access (IFDMA) PR system are monitored by a number of cognitive radio sensing nodes (CRSNs). These CRSNs distributedly detect the on/off states of users based on one of the three energy detection schemes. After the local spectrum sensing, the CRSNs transmit their detected states to a fusion centre (FC) with the aid of FH/MFSK techniques. At the FC, the on/off states of the users supported the IFDMA PR system are finally classified according to either the conventional equal-gain combining (EGC) scheme or the novel erasure-supported EGC (ES-EGC) scheme. In this way, the on/off information about the spectrums occupied by an IFDMA PR systemcan be obtained, so that they can be exploited by a cognitive radio (CR) system. For local spectrum sensing, in this paper, we consider four synchronisation scenarios concerning the synchronisation between the received IFDMA signals and the CRSNs. The performance of the FH/MFSK SSN associated with various schemes is investigated by simulations. Our studies show that the FH/MFSK SSN constitutes one of the highly reliable spectrum sensing schemes, which are capable of exploiting both the space diversity provided by local CRSNs and the frequency diversity provided by the subcarriers of IFDMA system.

  • Time Series Forecasting with Missing Values

    Appears in:
    cogcom 15(4): e5

    Authors:
    Shie-Jue Lee, Chia-Yung Chang, Shin-Fu Wu

    Downloads:
    3344

    Abstract:
    Time series prediction has become more popular in various kinds of applications such as weather prediction, control engineering, financial analysis, industrial monitoring, etc. To deal with real-world problems, we are often faced with missing values in the data due to sensor malfunctions or human errors. Traditionally, the missing values are simply omitted or replaced by means of imputation methods. However, omitting those missing values may cause temporal discontinuity. Imputation methods, on the other hand, may alter the original time series. In this study, we propose a novel forecasting method based on least squares support vector machine (LSSVM). We employ the input patterns with the temporal information which is defined as local time index (LTI). Time series data as well as local time indexes are fed to LSSVM for doing forecasting without imputation. We compare the forecasting performance of our method with other imputation methods. Experimental results show that the proposed method is promising and is worth further investigations.

  • Spectrum Occupancy Measurements in the 2.3-2.4 GHz band: Guidelines for Licensed Shared Access in Finland

    Appears in:
    cogcom 15(2): e2

    Authors:
    Juhani Hallio, Jan Engelberg, Dennis Roberson, Reijo Ekman, Juha Röning, Jani Auranen, Xianfu Chen, Marko Höyhtyä, Juha Kalliovaara, Ali Riaz, Tanim Taher, Marja Matinmikko

    Downloads:
    2054

    Abstract:
    This paper presents results from spectrum occupancy measurements in the 2.3-2.4 GHz band at Turku, Finland. The band is currently under study in European regulation and standardization for mobile communication systems. We review the recently introduced Licensed Shared Access (LSA) concept as a potential means for making the 2.3-2.4 GHz band available for mobile communications on a shared basis while protecting the rights of the incumbent spectrum users. The spectrum occupancy measurements conducted in one location in Finland show that the use of this band is rather low indicating that there might be potential for mobile communication systems to share this band with the incumbents under the LSA approach. Based on the obtained knowledge about the use of the studied band in Finland we create a set of guidelines for LSA to make the operation efficient both from the technical and economic viewpoint.

  • A Hardware Prototype of a Flexible Spectrum Sensing Node for Smart Sensing Networks

    Appears in:
    cogcom 16(6): e1

    Authors:
    Peter Lohmiller, Hermann Schumacher, Václav Valenta, Ahmed Elsokary

    Downloads:
    1750

    Abstract:
    In this paper we present a prototype for a spectrum sensing node for a cognitive radio sensing network. Our prototype consists of a custom down-conversion front-end with an RF input frequency range from 300 MHz to 3 GHz and a Power Spectral Density (PSD) estimation algorithm implemented on a Virtex-6 Field Programmable Gate Array (FPGA). The base-band processing part is capable of calculating the PSD for a bandwidth upto 245.76 MHz achieving a resolution of 60 kHz and an online variable averaging functionality with a maximum of 32767 averages. We show the arithmetic optimization techniques used for the PSD evaluation to optimize FPGA resource usage. Real time performance and calculation of the PSD for real world signals in the GSM downlink, DECT and the UHF DVB-T bands are demonstrated.

  • Frequency Modulation based Resistive Sensing for Wearable Galvanic Skin Response

    Appears in:
    cogcom 15(8): e3

    Authors:
    Mehmet Yuce, Jean-Michel Redoute, Md Shamsul Arefin

    Downloads:
    1629

    Abstract:
    This paper presents a frequency modulation based readout circuit for the measurement of skin conductance or resistance. A charge pump based frequency-to-voltage converter circuit with adjustable sensitivity is used to convert the frequency shifts due to skin resistance changes into voltage variations. The readout circuit improves the measurement accuracy and artifact rejection in measurements of the galvanic skin response on the skin, and can be integrated with wearable physiological monitoring systems. The readout circuit is designed and fabricated using the UMC 0.18 µm CMOS technology. It occupies an area of 0.18 mm2 and consumes 11.7 mW.

  • Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things

    Appears in:
    cogcom 15(2): e4

    Authors:
    R. Francisco, A.M. Arsenio

    Downloads:
    1609

    Abstract:
    Cognitive technologies can bring important benefits to our everyday life, enabling connected devices to do tasks that in the past only humans could do, leading to the Cognitive Internet of Things. Wireless Sensor and Actuator Networks (WSAN) are often employed for communication between Internet objects. However, WSAN face some problems, namely sensors’ energy and CPU load consumption, which are common to other networked devices, such as mobile devices or robotic platforms. Additionally, cognitive functionalities often require large processing power, for running machine learning algorithms, computer vision processing, or behavioral and emotional architectures. Cloud massive storage capacity, large processing speeds and elasticity are appropriate to address these problems. This paper proposes a middleware that transfers flows of execution between devices and the cloud for computationally demanding applications (such as those integrating a robotic brain), to efficiently manage devices’ resources.

  • WIFI/PDR indoor integrated positioning system in a multi-floor environment

    Appears in:
    cogcom 18(14): e2

    Authors:
    Maxim Dolgov, Mu Zhou, Yanmeng Wang, Yiyao Liu

    Downloads:
    1604

    Abstract:
    To improve the accuracy of indoor positioning for location-based services, we created an improved WiFi/PDR integrated positioning and navigation system where we are using Extended Kalman filter (EKF). The proposed algorithm first relies on MEMS in our mobile phone to estimate the velocity and heading angles of the target. Second, the velocity and heading angles, together with the results of WiFi fingerprinting-based positioning, are considered as the input of the EKF for the sake of conducting two-dimensional positioning. Third, the proposed algorithm calculates the altitude of the target by using the real-time recorded barometer. The results of our experiments show that integrated navigation system using Extended Kalman filter can effectively eliminate the accumulated errors in the PDR positioning algorithm and can reduce the influence of the large-scale jump of the WiFi fingerprint positioning result brought by the RSSI disturbance on the positioning accuracy of the system.

  • Performance Analysis on the Coexistence of Multiple Cognitive Radio Networks

    Appears in:
    cogcom 15(2): e1

    Authors:
    Riku Jäntti, Oluwaseyi Omotere, Lijun Qian

    Downloads:
    1602

    Abstract:
    The demand for wireless services is growing on a daily basis while spectral resources to support this growth are static. Therefore, there is need for the adoption of a new spectrum sharing paradigm. Cognitive Radio (CR) is a revolutionary technology aiming to increase spectrum utilization through dynamic spectrum access, as well as mitigating interference among multiple coexisting wireless networks. In many practical scenarios, multiple CR networks may coexist in the same geographical area, and they may interfere with each other and also have to yield to the primary user (PU). In this study, we investigate how much throughput a node in a CR network can achieve in the presence of another CR network and a PU. The results of this study illustrate how the transmission probability and sensing performance affect the achievable throughput of a node in coexisting CR networks. In addition, these results may serve as guidance for the deployment of multiple CR networks.

  • Miniaturized Implantable DS-PIFA Antenna for Biomedical Applications

    Appears in:
    cogcom 15(8): e4

    Authors:
    Farhad Gozasht, Ananda Mohan

    Downloads:
    1578

    Abstract:
    This paper presents an implantable miniaturized planar inverted-F antenna (PIFA) for biomedical applications. We propose small sized PIFA that can operate over 2.45 GHz Industrial, Scientific, and Medical (ISM) band. We have investigated the effect of antenna parameters on resonant frequencies using empirical parametric studies and achieved highly compact PIFA antenna occupies a volume of 92 mm3 with a size of 8.1×7.1×1.6 mm3. Moreover, the effects of the variation of surrounding environment such as skin and fat thickness on the antenna performance are also considered. The impedance characteristics of the proposed antennas are measured using experimental tissue mimicking phantoms. We have also evaluated the calculated Specific Absorption Rate (SAR) by using an indirect thermal method to measure the SAR inside the mimicking phantom.

  • Research on Intelligent anti-jamming communication with Cognitive Radio

    Appears in:
    cogcom 18(14): e1

    Authors:
    Jingning Wang, Yi Zhang, Meng Liu

    Downloads:
    1550

    Abstract:
    In order to solve the interfere problem in complex electromagnetic environment, NC-OFDM and TDCS are efficient transmit wave form proposed for cognitive radio. The spectral efficiency and the applicable environment of TDCS are different from NC-OFDM. The simulation results show that NC-OFDM can obtain the higher spectral efficiency and the required SINR is higher, and TDCS can work well in lower SINR environment with different spreading factor. When there is little spectrum hole, spread spectrum is a better choice. There is no threshold of some parameter which can make decision. An artificial intelligence algorithm is proposed to select the optimal one from several wave forms. The input parameters of the algorithm include SINR, interference bandwidth, spectrum holes, etc.
Publisher
EAI
ISSN
2313-4534
Number of Volumes
4
Last Published
2019-01-14
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