Radio access technology selection strategies in next generation wireless networks
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NO FULL TEXT AVAILABLE. Access is restricted indefinitely. ----- Next Generation Wireless Networks (NGWNs) are expected to be heterogeneous networks which integrate all different Radio Access Technologies (RATs) through a common platform. A major challenge is how to allocate users to the most suitable RAT for them. An optimized solution can maximize the efficient use of radio resources, achieve better performance for service providers and provide Quality of Service (QoS) with low costs to users. Current Radio Resource Management (RRM) is implemented efficiently for homogeneous networks such as GSM/EDGE Radio Access Network (GERAN) and UMTS Terrestrial Radio Access Network (UTRAN). However, RRM is not suitable for heterogeneous networks. Common RRM (CRRM) was proposed to manage radio resource utilization in the heterogeneous wireless network. RAT selection algorithms are part of the CRRM algorithms. Simply, their role is to verify if a new or handover (HO) incoming call will be suitable to fit into a heterogeneous wireless network, and to decide which of the available RATs is most suitable to fit the need of the incoming call and admit it. Guaranteeing the requirements of QoS for all accepted calls and at the same time being able to provide the most efficient utilization of the available radio resources is the goal of the RAT selection algorithm. The RAT selection algorithm can be implemented in one of three different approaches: centralized, distributed (terminal controlled) or hybrid (terminal controlled with network assistance). A centralized RAT selection algorithm has the benefit of considering more criteria in making the RAT selection decision. However, it reduces network capacity. A distributed RAT selection algorithm has the benefit of allowing User Terminals (UTs) to select the most efficient RAT that maximizes the users’ satisfaction and has the benefit of minimizing the management workload in the network equipment by distributing some of them to the UTs. However, it will lead to inefficient radio resource utilization as users do not have the required information about cell load and network policies and preferences. This problem can be solved by using a terminal controlled RAT selection algorithm with network assistance, where the network will assist the Uts in making the RAT selection decision by providing information related to the network. This thesis proposes an innovative Smart Mobile Communication approach which consists of four intelligent hybrid algorithms to allow users with smart devices to select their preferences for new or vertical HO (VHO) calls which vary between choosing best QoS, cheapest cost, power efficiency or mobility optimization connections. The proposed approach is simulated in multi-access scenarios and analytically evaluated in a multi-dimensional Markov chain model which has been developed for this purpose and then compared with centralized and distributed algorithms. Simulation and analytical results show that the proposed algorithms are more efficient than the centralized and distributed algorithms.
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