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Regular monitoring of vital signs guarantees a preventive treatment of common diseases ensuring better health for people. Most of the proposed solutions in e-health context are based on a set of heterogeneous wireless sensors, fitting the patient and his environment. Often, these sensors are connected to a local smart node acting as a gateway to the outside (contacts, servers). When the patient is mobile, one of the issues we may face is the guarantee of a permanent connectivity between local smart node and the outside. To overcome this problem, we need to define a robust communications architecture able to benefit from different technologies and standards. This provides equipments with the ability to dispose of free-bands to perform their transmission anytime and anywhere. Cognitive radio, although appropriate technology, requires taking into account the interdependence between the patient's mobility and frequency band changes. Our proposal, is an anticipation model, a decision-making function that predicts the state of frequency bands occupancy. The model combines the machine learning techniques to the Grey Model system to provide low cost algorithm for spectral prediction which facilitates or guarantees permanent connectivity.

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Abstract-Transmissions of multimedia data in emergency context such as, the occurrence of trauma or stroke are sensitive to the network delay, throughput and packet loss. Depending on the urgency, the communication channel quality can decide the survival of a patient. For saving lives, network infrastructure offering good Quality of Service (QoS), high broadband and low communication cost must be considered. In this context, Cognitive Radio Networks (CRN) seem appropriate. Indeed, this technology is well suited with its sensing ability and the scanning of a wide range of technologies, for assigning adequate frequency bands which meet the application constraints. In this paper, we propose a CRN-framework and an associated analytical tool that sets and imposes constraints to be respected, for ensuring reliable and high quality end-to-end communications.

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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 from low cost access networks. Cognitive Radio will be used to manage the selection/switching across different frequency UHF/VHF bands or TV White Spaces (TVWS), while avoiding interference.