Mobility Aware Network Selection in a Heterogeneous Wireless Environment

Abstract

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).

A machine learning access network selection in a heterogeneous wireless environment

“…The range of values for these parameters is displayed in Table 2 and are obtained through simulations. 15,16,22 The simulations were carried out in different scenarios for the different applications (loaded or empty cells, different number of users, users at the middle of the cell and other at the edge where the RSS is very low). This is why we have for each parameter a range of values and for the sake of simulation we take an average value.…”

“…So, the weight values for each simulation represent the apps requirements Secondly, we require the instantaneous quality of service data for all the RATs. The range of values for these parameters is displayed in Table 2 and are obtained through simulations 15,16,22 . The simulations were carried out in different scenarios for the different applications (loaded or empty cells, different number of users, users at the middle of the cell and other at the edge where the RSS is very low).…”

“…• The user equipment criteria: It encompasses details about the costumer mobile phone. 16 F I G U R E 2 Network selection process. 5 The RAN selection operation is initiated by a mobile device when it needs to establish a connection to a wireless network, such as when a user wants to make a call, send a message, or access the internet.…”

“…Authors in Reference 16 proposed a new framework for network selection; their solution depends on path prediction (performed using a Markov model) coupled with the modified‐SAW method. Their results are interesting because they reduce the Vertical Hand‐off (VH) occurrences.…”

“…These criteria can be categorized into four types, as outlined in the Reference 5 (Figure 2). Network feature criteria: This category provides information on various network features, such as network bandwidth, covered region, connectivity time, and data rate. Application criteria: This category provides information on the requirements of the application to function optimally, including thresholds for normal conditions, delay, jitter, and packet loss rate. User preference criteria: This category provides information on user‐specific factors, such as the user's cost constraints and whether they prioritize cost over quality or vice versa. The user equipment criteria: It encompasses details about the costumer mobile phone 16 …”