Heterogeneous wireless networks is a term referring to networks combining different radio access technologies with the aim of establishing the best connection possible. In this case, users with multi-mode terminals can connect via different wireless technologies, such as 802.16, 802.11, UMTS, HSPA and LTE, all at the same time. The problem consists in the selection of the most suitable from all radio access technologies available. The decision process is called network selection, and depends on several parameters, such as quality of service, mobility, cost, energy, battery life, etc. Several methods and approaches have been proposed in this context, with their objective being to offer the best QoS to the users, and/or to maximize re-usability of the networks. This paper represents a survey of the network selection methods used. Multiple attribute-dependent decision-making methods are presented. Furthermore, the game theory concept is illustrated, the use of the fuzzy logic is presented, and the utility functions defining the network selection process are discussed.

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In the context of heterogeneous networks, users with multi-mode terminals can connect to different radio access technologies such as 802.16, 802.11, HSPA and LTE at the same time. The challenge here is to achieve the Always Best Connected ABC concept; the main issue is the automatic choice of the suitable Radio Access Technology RAT from the list of the available RATs. This decision is called the network selection. In this paper, we propose a modified-SAW function to deal with the drawbacks of the existing solutions. Indeed, the existing MADMs methods suffer mainly from the famous problem of rank reversal once an alternative is added or removed, other problems occur in the legacy MADMs such as the sensitiveness to the user preference in TOPSIS; the penalization of the alternatives with poor attributes values in WPM. Our simulations brought out the lakes of the traditional MADMs approach in the context of network selection. We modify the SAW method intelligently and we use it to solve the network selection problem. Finally, we compare the performance of our solution with the previous works in different scenarios; the simulations show that our proposal outperforms the other existing methods.

Different Radio Access Technologies (RATs) coexist in the same area has encouraged the researchers to get profit from the available networks by selecting of the best RAT at each moment of the call session to satisfy the user requirements. In this paper, we address a real-world problem which is the frequent mobility of the users in heterogeneous networks. We present in this paper a framework that allows users to select the best networks for the whole call session especially form a mobility perspective. The framework consists of several steps, starting by the path prediction which is performed using a Markov model order 2. The second step is to make the network selection on the zones of each predicted path, while in the third step; we get the best RAT’s configuration for each predicted path. Finally, we use another function to select one of the best configurations to be used for all the possible used paths. The results show that our proposal performs very well by eliminating the unnecessary vertical handover while maintaining a good Quality of Service (QoS).

This paper will center mainly on the PS part of the RRM task, which performs the radio resource allocation in both uplink and downlink directions. Several approaches and algorithms have been proposed in the literature to address this need (allocate resources efficiently), the diversity and multitude of algorithms is related to the factors considered for the optimal management of radio resource, specifically, the traffic type and the QoS (Quality of Service) requested by the UE.In this article, an art's state of the radio resource allocation strategies and a detailed study of several scheduling algorithms proposed for LTE (uplink and downlink) are made. Therefore, we offer our evaluation and criticism.