Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Recent advances in radio resource management for heterogeneous LTE/LTE-A networks

As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies

Game theoretical models for clustering and resource sharing in macro-femtocells networks

One of the main challenges of cellular network operators is to keep a good network quality for their users. In most cases, network quality decreases in indoor environments causing users to switch from one operator to another. A promising solution to cope with this issue is the deployment of femtocells that are used mainly at homes to enhance the mobile network coverage. In fact, higher penetration of broadband and mobile phones with high requirements of new applications such as video conferencing and internet games are promoting femtocell market. However, the deployment of femtocells in existing macrocell networks is a very challenging task due to the high complexity of the resource allocation. In this thesis, we focus on proposing several solutions to address the resource allocation problem in macro-femtocell networks with dense deployment of femtocells based on clustering techniques. Clustering techniques are used to reduce the resource allocation complexity of dense-femtocell networks since the resources are allocated locally within each cluster. Furthermore, a cluster head is responsible for the allocation of resources to femtocells within the cluster which avoids the co-tier interference. The clustering techniques have been widely used for distributed resource allocation in heterogeneous networks through the use of game theory models. In this work, three distributed resource allocation algorithms based on cooperative and evolutionary games are proposed. In the first part, we discuss the resource allocation problem for the non-dense deployment of femtocells. Toward this goal, a coalitional game is used to incentive femtocells in the formation of clusters. The approach decomposes in: (i) a base station selection algorithm for public users, (ii) a clustering algorithm based on cooperative game theory and (iii) a resource allocation within each cluster based on the PSO technique. Besides, an interference control mechanism enabled femtocells to leave its current cluster when the interference levels are higher than an interference threshold. In the second part, we focus on a fair allocation of resources for macro-femtocell networks. We develop a clustering algorithm based on a cooperative game for non-dense femtocell network. The Shapley value is applied to find the marginal contribution of every femtocell to all the possible groups of femtocells, thus, finding the fair amount of resources to be allocated to each femtocell within a cluster. This solution is only applied for non-dense femtocell deployment due to that the complexity of calculating the Shapley value increases significantly with a large number of femtocells. Stability criteria based on the ε-concept of game theory is utilized to find the set of stable clusters. Finally, the analysis of the resource allocation for dense-femtocell deployment is addressed through an evolutionary game theory (EGT) model. It is assumed that EGT requires bounded rationality from players, this reduces the complexity and allows the dense deployment of femtocells. In addition, we demonstrate that the set of clusters formed with EGT are stable by means of the replicator dynamics. The proposed model also includes system analysis for users with low mobility such as pedestrians and cyclists

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

コグニティブネットワークとヘテロジニアスネットワークの協調によるスペクトルの効率的利用に関する研究

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 瀬崎 薫, 東京大学教授 浅見 徹, 東京大学教授 江崎 浩, 東京大学准教授 川原 圭博, 東京大学教授 森川 博之, 東京大学教授 相田 仁University of Tokyo(東京大学

Fair resource allocation with interference mitigation and resource reuse for LTE/LTE-A femtocell networks

Joint consideration of interference, resource utilization, fairness, and complexity issues is generally lacking in existing resource allocation schemes for Long-Term Evolution (LTE)/LTE-Advanced femtocell networks. To tackle this, we employ a hybrid spectrum allocation approach whereby the spectrum is split between the macrocell and its nearby interfering femtocells based on their resource demands, whereas the distant femtocells share the entire spectrum. A multiobjective problem is formulated for resource allocation between femtocells and is decomposed using a lexicographic optimization approach into two subproblems. A greedy algorithm of reasonably low complexity is proposed to solve these subproblems sequentially. Simulation results show that the proposed scheme achieves substantial throughput and packet loss improvements in low-density femtocell deployment scenarios while performing satisfactorily in high-density femtocell deployment scenarios with substantial complexity and overhead reduction. The proposed scheme also performs nearly as well as the optimal solution obtained by exhaustive search

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio

In-Building Capacity Enhancement using Small Cells in Mobile Networks: An Overview

In this paper, we give an overview of the state-of-the-art research studies to present the potential of small cells to address the high capacity demands of in-building users in mobile networks. In doing so, we discuss relevant theoretical backgrounds and carry out performance evaluations of key enabling technologies along with three major directions toward improving the network capacity, including spectrum accessibility, Spectral Efficiency (SE) improvement, and network densification. For the spectrum accessibility, numerous types of Small Cell Base Station (SBS) architectures of a Mobile Network Operator (MNO) are evaluated. For the SE improvement, cognitive radio techniques are evaluated for the Dynamic Spectrum Sharing (DSS) among multiple MNOs in a country. For the network densification, the spectrum reuse is evaluated at both intra-and inter-building levels for a given Co-Channel Interference (CCI) constraint. It is shown that multi-band multi-transceiver enabled small cells operating in the high-frequency millimeter-wave licensed or unlicensed spectrum to realize DSS techniques by exploiting SBS architectures for the spectrum accessibility, a hybrid interweave-underlay spectrum access in Cognitive Radio Networks for the spectral efficiency improvement, and both vertical and horizontal spectrum reuse in small cells deployed densely within buildings for the network densification can address high capacity demand in indoor mobile networks