Spectrally and Energy Efficient Radio Resource Management for Multi-Operator Shared Networks

Commercial mobile communication systems are mainly based on licensed frequency spectrum, and the license is very expensive as the spectrum is a sparse wireless resource. Therefore, sharing this wireless resource is an essential requirement not only at the present but also in the future considering trends like connectivity for everybody and everything. In this thesis, we study the sharing of wireless resources with different approaches for realizing fair, efficient, and predictable sharing solutions in a controlled manner. The efficient use of wireless channel resources is an important target to reduce the costs of network operation and deployment. To achieve this, we need practical scheduling algorithms for wireless resources, out of which several of them will be presented and analyzed in this work. Different optimization frameworks for the spectral efficiency utility are presented, with an individual focus on guaranteeing resource or rate fairness among the operators in a network with shared radio resources. Thus, the presented proposals will help the mobile network operators to overcome the issues of losing network control and traceability of used wireless resources in a shared environment. Besides this, emerging vertical industries, such as automotive, healthcare, industry 4.0, internet of things (IoT) industries will put a certain burden on the wireless networks asking for guaranteed service level requirement from the mobile network operators. In this regard, this thesis provides the necessary methods addressing these challenges with the help of scheduling methods which are based on the joint optimization of spectral and energy efficiency. Thus, wireless networks will be enabled as a service function in a controlled and scalable way for new emerging markets. Furthermore, the presented solutions t well with the requirements of fifth generation (5G) network slicing

Enhancing cooperation in wireless networks using different concepts of game theory

PhDOptimizing radio resource within a network and across cooperating heterogeneous networks is the focus of this thesis. Cooperation in a multi-network environment is tackled by investigating network selection mechanisms. These play an important role in ensuring quality of service for users in a multi-network environment. Churning of mobile users from one service provider to another is already common when people change contracts and in a heterogeneous communication environment, where mobile users have freedom to choose the best wireless service-real time selection is expected to become common feature. This real time selection impacts both the technical and the economic aspects of wireless network operations. Next generation wireless networks will enable a dynamic environment whereby the nodes of the same or even different network operator can interact and cooperate to improve their performance. Cooperation has emerged as a novel communication paradigm that can yield tremendous performance gains from the physical layer all the way up to the application layer. Game theory and in particular coalitional game theory is a highly suited mathematical tool for modelling cooperation between wireless networks and is investigated in this thesis. In this thesis, the churning behaviour of wireless service users is modelled by using evolutionary game theory in the context of WLAN access points and WiMAX networks. This approach illustrates how to improve the user perceived QoS in heterogeneous networks using a two-layered optimization. The top layer views the problem of prediction of the network that would be chosen by a user where the criteria are offered bit rate, price, mobility support and reputation. At the second level, conditional on the strategies chosen by the users, the network provider hypothetically, reconfigures the network, subject to the network constraints of bandwidth and acceptable SNR and optimizes the network coverage to support users who would otherwise not be serviced adequately. This forms an iterative cycle until a solution that optimizes the user satisfaction subject to the adjustments that the network provider can make to mitigate the binding constraints, is found and applied to the real network. The evolutionary equilibrium, which is used to 3 compute the average number of users choosing each wireless service, is taken as the solution. This thesis also proposes a fair and practical cooperation framework in which the base stations belonging to the same network provider cooperate, to serve each other‘s customers. How this cooperation can potentially increase their aggregate payoffs through efficient utilization of resources is shown for the case of dynamic frequency allocation. This cooperation framework needs to intelligently determine the cooperating partner and provide a rational basis for sharing aggregate payoff between the cooperative partners for the stability of the coalition. The optimum cooperation strategy, which involves the allocations of the channels to mobile customers, can be obtained as solutions of linear programming optimizations