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![Table 1 . TVWS frequency bands [2]](profile/Dramane-Ouattara/publication/276262093/figure/tbl1/AS:670006564102160@1536753421317/TVWS-frequency-bands-2_Q320.jpg)
![Figure 2. Google balloons for Internet in rural areas [4]](profile/Dramane-Ouattara/publication/276262093/figure/fig2/AS:670006559899660@1536753420709/Google-balloons-for-Internet-in-rural-areas-4_Q320.jpg)
![Figure 4. Network coverage map in Côte d'Ivoire [10]](profile/Dramane-Ouattara/publication/276262093/figure/fig4/AS:670006559924250@1536753420875/Network-coverage-map-in-Cote-dIvoire-10_Q320.jpg)
In this paper, we propose a new approach based on Cognitive Radio technology to address the challenges for ensuring connectivity in remote areas of Africa. Indeed, the current network coverage is concentrated around the cities with high density of population. Through the deployment of Cognitive Radio, emergency services in rural areas will benefit...
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Context 1
... test the frequency hopping, we generate a disruptive AWGN (Adds White Gaussian Noise) signal to create interferences on the transmission channel.The signal thus generated is seen as a transmission of a primary node. This then triggers the process of frequency hopping to avoid interferences as seen in figure 9. This experiment in GSM and WiFi bands remains valid for mitigating interferences to TV band users with cognitive radio networks deployed in rural areas. ...
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Citations
The integration of Information and Communication Technologies (ICTs) into the medical field has, among other things, promoted innovation in diagnostics and in tracking patients and also given rise to the world of “e‐health”. The e‐health designates the use of ICT for all healthcare activities and the concept integrates telemedicine, tele‐health as well as other digital healthcare solutions. This chapter describes e‐health systems through the examples of some known European projects in this field. As several studies, implementations and simulations have shown, e‐health systems need to manage Quality of Service (QoS) and security in order to respond to the requirements of the e‐health services and to be able to resist malicious attacks. The chapter discusses the QoS control and security management.
The aging of the population will probably catalyze the rise of chronic diseases and could intensify the need for personal assistance solutions. While researchers are focusing on information and communication technologies to provide responses to these public health problems, the number of connected objects is experiencing a rapid expansion. Indeed, desired revolution of technologies for health, forprevention and disease treatment coincides with the development of the Internet of Things 2. Thus, technological innovations and medical progress, for making it possible to monitor pathologies, often chronic, anywhere need appropriate equipments. Also, remote and real-time patient monitoring applications would require more network resources. In this context, communication resources management/sharing, technologies and equipments compatibilities and aplication’s desired performances become significant challenges. In this thesis, we propose an architecture based on Cognitive Radio, for meeting the medical applications constraints. We also analyze and test three important criteria for emergency transmissions, using this architecture.Connectivity : Any solution for patients monitoring must have anywhere and anytime capabilities for care continuity needs. High availability of network services and quality offered are critical for patient telemonitoring. We propose in this context, a spectral prediction mechanism able to examine the occupation conditions of the frequency bands. The algorithm we propose, associated learning and Grey Model technique in order to deal with any network connection discontinuities.Interference management : Network equipments must be able to perceive or to analyze their environment and act according to the underlying constraints. The interest is to protect in our case, medical equipment which are very sensitive to noise. Patient monitoring becomes possible at home or in the hospital, for example, with an acceptable level of interference. We propose for this criterion evaluation, a Cognitive Radio Networks deployment model in a hospital area. We define examples of functions for dynamic adaptation of the communication parameters, depending on the nearby medical devices sensitivity.Transmission efficiency under multimedia content delivery : This criterion analizes the ability of the architecture to provide desired quality in multimedia content delivery for real-time assistance or diagnosis. Patient monitoring at home or an emergency event may require the transmission of image or audio content to the hospital center. The remote monitoring solution must be able to provide these facilities which require a broadband network. We suggest an algorithm for resource reservation that performs a better management of the quality of service for medical multimedia content. We combine this algorithm with a transmission parameters control methode for maintaining the QoS at an acceptable level.
