Access Network Selection in Heterogeneous Networks

The future Heterogeneous Wireless Network (HWN) is composed of multiple Radio Access Technologies (RATs), therefore new Radio Resource Management (RRM) schemes and mechanisms are necessary to benefit from the individual characteristics of each RAT and to exploit the gain resulting from jointly considering the whole set of the available radio resources in each RAT. These new RRM schemes have to support mobile users who can access more than one RAT alternatively or simultaneously using a multi-mode terminal. An important RRM consideration for overall HWN stability, resource utilization, user satisfaction, and Quality of Service (QoS) provisioning is the selection of the most optimal and promising Access Network (AN) for a new service request. The RRM mechanism that is responsible for selecting the most optimal and promising AN for a new service request in the HWN is called the initial Access Network Selection (ANS). This thesis explores the issue of ANS in the HWN. Several ANS solutions that attempt to increase the user satisfaction, the operator benefits, and the QoS are designed, implemented, and evaluated. The thesis first presents a comprehensive foundation for the initial ANS in the H\VN. Then, the thesis analyses and develops a generic framework for solving the ANS problem and any other similar optimized selection problem. The advantages and strengths of the developed framework are discussed. Combined Fuzzy Logic (FL), Multiple Criteria Decision Making (MCDM) and Genetic Algorithms (GA) are used to give the developed framework the required scalability, flexibility, and simplicity. The developed framework is used to present and design several novel ANS algorithms that consider the user, the operator, and the QoS view points. Different numbers of RATs, MCDM tools, and FL inference system types are used in each algorithm. A suitable simulation models over the HWN with a new set of performance evolution metrics for the ANS solution are designed and implemented. The simulation results show that the new algorithms have better and more robust performance over the random, the service type, and the terminal speed based selection algorithms that are used as reference algorithms. Our novel algorithms outperform the reference algorithms in- terms of the percentage of the satisfied users who are assigned to the network of their preferences and the percentage of the users who are assigned to networks with stronger signal strength. The new algorithms maximize the operator benefits by saving the high cost network resources and utilizing the usage of the low cost network resources. Usually better results are achieved by assigning the weights using the GA optional component in the implemented algorithms

Congestion control in multi-serviced heterogeneous wireless networks using dynamic pricing

Includes bibliographical references.Service providers, (or operators) employ pricing schemes to help provide desired QoS to subscribers and to maintain profitability among competitors. An economically efficient pricing scheme, which will seamlessly integrate users’ preferences as well as service providers’ preferences, is therefore needed. Else, pricing schemes can be viewed as promoting social unfairness in the dynamically priced network. However, earlier investigations have shown that the existing dynamic pricing schemes do not consider the users’ willingness to pay (WTP) before the price of services is determined. WTP is the amount a user is willing to pay based on the worth attached to the service requested. There are different WTP levels for different subscribers due to the differences in the value attached to the services requested and demographics. This research has addressed congestion control in the heterogeneous wireless network (HWN) by developing a dynamic pricing scheme that efficiently incentivises users to utilize radio resources. The proposed Collaborative Dynamic Pricing Scheme (CDPS), which identifies the users and operators’ preference in determining the price of services, uses an intelligent approach for controlling congestion and enhancing both the users’ and operators’ utility. Thus, the CDPS addresses the congestion problem by firstly obtaining the users WTP from users’ historical response to price changes and incorporating the WTP factor to evaluate the service price. Secondly, it uses a reinforcement learning technique to illustrate how a price policy can be obtained for the enhancement of both users and operators’ utility, as total utility reward obtained increases towards a defined ‘goal state’

Common Radio Resource Management: Joint Call Admission Control And Traffic Offloading Method

The concept of Common Radio Resource Management (CRRM) has been proposed by 3GPP in order to efficiently manage the common pool of radio resources that are available for each of the existing radio access technologies in the heterogeneous wireless networks (HWNs). The main challenge of CRRM for HWNs is to search the best connection for the demanded services, enabling calls transference from one interface to another seamlessly and utilizing the availability of all radio resources. Thus, this thesis proposes a joint call admission control (JCAC) and traffic offloading algorithms in the CRRM for an integrated cellular and mobile network. The contributions of this work are threefold. First, a user mobility model in the wireless overlay network is proposed

Best Operator Policy in a Heterogeneous Wireless Network

In this paper, we perform a business analysis of our hybrid decision algorithm for the selection of the access in a multi-operator networks environment. We investigate the ability of the operator to express his strategy and influence the access selection for his client. In this purpose, we study two important coefficients of the previously proposed cost function, Wu and Wop, and show that the value of these coefficients is not arbitrary. Simulation results show that the value of the ratio Wu/Wop enables a selection decision respecting operator's strategy and it affects the achieved global profit for all cooperating operators.Comment: ICeND, Beyrouth : Lebanon (2014

Green Symbiotic Cloud Communications: Virtualized Transport Layer and Cognitive Decision Function

The evolution of the concept of cloud communications has posed a growing emphasis on virtual and abstract environments for the flow of information, structuring it in similitude to a natural cloud. The Green Symbiotic Cloud Communications (GSCC) paradigm created on this concept facilitates the use of multiple communication mediums concomitantly creating a first of its kind communication cloud. This paper specifically corroborates a virtualized transport layer and network ports and an abstracted Internet protocol scheme in defining the GSCC architecture. We further address the issue of formulating a cognitive decision function based on utility theory, which allows users with GSCC enabled devices to intelligently distribute its bandwidth requirement amongst the available communication mediums. Considering the multiple criteria associated with different networks we formulate an optimization problem to find the solution for this resource allocation problem for single user. We further address the multi-user scenario and formulate and solve the multi-objective optimization problem using goal attainment technique. Results in single and multiple user scenarios, demonstrate that by utilizing multiple mediums as per GSCC paradigm coupled with our proposed decision function improves the functionality of the communication cloud. The proposed architecture is dynamic and evolving, embedding greenness by efficiently utilizing the available resources as and when required. The multiple virtual links equate a linearly increasing relationship with the throughput achieved. Experimental results for both real time and static data through the proposed schematic are documented. The augmented paradigm enhances the quality of service, linearly increases throughput and increases the overall security in communications

An intelligent radio access network selection and optimisation system in heterogeneous communication environments

PhDThe overlapping of the different wireless network technologies creates heterogeneous communication environments. Future mobile communication system considers the technological and operational services of heterogeneous communication environments. Based on its packet switched core, the access to future mobile communication system will not be restricted to the mobile cellular networks but may be via other wireless or even wired technologies. Such universal access can enable service convergence, joint resource management, and adaptive quality of service. However, in order to realise the universal access, there are still many pending challenges to solve. One of them is the selection of the most appropriate radio access network. Previous work on the network selection has concentrated on serving the requesting user, but the existing users and the consumption of the network resources were not the main focus. Such network selection decision might only be able to benefit a limited number of users while the satisfaction levels of some users are compromised, and the network resources might be consumed in an ineffective way. Solutions are needed to handle the radio access network selection in a manner that both of the satisfaction levels of all users and the network resource consumption are considered. This thesis proposes an intelligent radio access network selection and optimisation system. The work in this thesis includes the proposal of an architecture for the radio access network selection and optimisation system and the creation of novel adaptive algorithms that are employed by the network selection system. The proposed algorithms solve the limitations of previous work and adaptively optimise network resource consumption and implement different policies to cope with different scenarios, network conditions, and aims of operators. Furthermore, this thesis also presents novel network resource availability evaluation models. The proposed models study the physical principles of the considered radio access network and avoid employing assumptions which are too stringent abstractions of real network scenarios. They enable the implementation of call level simulations for the comparison and evaluation of the performance of the network selection and optimisation algorithms

Network access selection in heterogeneous wireless networks

In heterogeneous wireless networks (HWNs), both single-homed and multi-homed terminals are supported to provide connectivity to users. A multiservice single-homed multi-mode terminal can support multiple types of services, such as voice call, file download and video streaming simultaneously on any one of the available radio access technologies (RATs) such as Wireless Local Area Network (WLAN), and Long Term Evolution (LTE). Consequently, a single-homed multi-mode terminal having multiple on-going calls may need to perform a vertical handover from one RAT to another. One of the major issues in HWNs is how to select the most suitable RAT for multiple handoff calls, and the selection of a suitable RAT for multiple-calls from a single-homed multi-mode terminal in HWNs is a group decision problem. This is because a single-homed multi-mode terminal can connect to only one RAT at a time, and therefore multiple handoff calls from the terminal have to be handed over to the same RAT. In making group decision for multiple-calls, the quality of service (QoS) requirements for individual calls needs to be considered. Thus, the RAT that most satisfies the QoS requirements of individual calls is selected as the most suitable RAT for the multiple-calls. Whereas most research efforts in HWNs have concentrated on developing vertical handoff decision schemes for a single call from a multi-mode terminal, not much has been reported in the literature on RAT-selection for multiple-calls from a single-homed multi-mode terminal in next generation wireless networks (NGWNs). In addition, not much has been done to investigate the sensitivity of RAT-selection criteria for multiple-calls in NGWNs. Therefore, this dissertation addresses these issues by focusing on following two main aspects: (1) comparative analysis of four candidate multi-criteria group decision-making (MCGDM) schemes that could be adapted for making RAT-selection decisions for multiple-calls, and (2) development of a new RAT-selection scheme named the consensus RAT-selection model. In comparative analysis of the candidate RAT-selection schemes, four MCGDM schemes namely: distance to the ideal alternative-group decision making (DIA-GDM), multiplicative exponent weighting-group decision making (MEW-GDM), simply additive weighting-group decision making (SAW-GDM), technique for order preference by similarity to Ideal solution-group decision making (TOPSIS-GDM) are considered. The performance of the multiple-calls RAT-selection schemes is evaluated using the MATLAB simulation tool. The results show that DIA-GDM and TOPSIS-GDM schemes are more suitable for multiple handoff calls than SAW-GDM and MEW-GDM schemes. This is because they are consistent and less-sensitive in making RAT-selection decision than the other two schemes, with regards to RAT-selection criteria (service price, data rate, security, battery power consumption and network delay) in HWNs. In addition, the newly developed RAT-selection scheme incorporates RAT-consensus level for improving RAT-selection decisions for multiple-calls. Numerical results conducted in MATLAB validate the effectiveness and performance of the newly proposed RAT-selection scheme for multiple-calls in HWNs