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The next generation mobile system is expected to support the continuous increase of users requirements. Through the high flow rates of these networks, new applications constraints are more complex and may be change dynamically and rapidly for wireless systems. The service heterogeneity provided by these applications has a great influence on system performance in terms of ability, availability and the context aware provided to make handover decision. To facilitate the negotiation process between the user and the network, we define some class of service that guarantees QoS for interworking between 3GPP and non-3GPP networks and the critical context criteria which influence the handover decision. In this context, our proposed approach supports the interaction between context-aware and class of service considering the use of the particular features of each class of service to make handover decision and providing the application required QoS. In this paper we conceive a new approach, called Enhance Simple Additive Weighting, for network selection that reduces computational complexity, the handover latency and eliminates networks which do not satisfy a minimum requirement compared to other existing approaches based on AHP strategy.

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International audienceThis paper presents a new cross-layer (PHY/MAC) resource allocation scheme based on Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) system with a multi-service (MS) and a multiuser (MU) configuration. It is about a downlink transmission chain based on the IEEE 802.16m specifications, in which the available resources (power and bandwidth) are dynamically allocated according to the system parameters such as Channel State Information (CSI), spectral efficiency, error code corrector rate, Quality of Service (QoS) requirements and services scheduling. The specificity of our system is the joint parameterization of these elements according to the total power and threshold rate constraints in order to guarantee a good trade-off between users QoS requirements and sub-carriers distribution. Simulation results show that the proposed scheme offers better performances in terms of average throughput and users satisfaction than previous resource allocation schemes

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