User Centric Interference Management in Wireless Networks (UCIMa)

为了满足越来越多的无线设备及其对增加的数据速率的需求，将部署异构密集无线网络。由于共存，一个挑战是干扰。在UCIMa项目的最后一部分，我们将重点关注异构网络的一个实例，即混合接入femto蜂窝网络。许多运营商已经推出了femtocell服务，包括沃达丰、SFR、AT&T、Sprint Nextel、Verizon和Mobile TeleSystems。飞蜂窝接入点（FAP），也称为家庭基站（BS），通过回程数字用户线路（DSL）、光纤或其他高速连接连接到运营商的宏蜂窝网络。从UCIMa项目前两阶段的理论研究出发，我们将把研究结果应用于飞蜂窝网络的混合接入框架。在这一阶段，该项目旨在从根本上研究macrocell和femtocell之间混合接入的经济框架。建立二层混合接入的物理层资源分配的市场模型。在混合接入的移动蜂窝网络中，干扰是一个值得关注的问题，因为FAP服务的移动蜂窝用户和未注册的宏蜂窝用户会竞争资源。此外，FAP服务的宏用户可以对MBS下的其他宏用户产生干扰而没有任何风险。从博弈论的角度来看，用户有动机欺骗他们的私人信息，例如通道状态信息（CSI），以获得更好的效用。研究了用户在MBS和FAP之间自由迁移的混合接入模式下的干扰和欺骗问题。我们在第二阶段扩展了该框架，以分析存在敌对用户的无线网络优化情况下的收敛和分散学习。分析了一种带有恶意用户的迭代分布式定价算法的动态特性和收敛性。其次，放宽了第二阶段中恶意用户拥有自私用户效用函数信息的假设，分析了恶意用户应用基于回归的迭代学习方案的场景。考虑到用户的传输能源成本，我们建议将第二阶段WP3的工作扩展为贝叶斯分析。此外，我们的目标是获得与VCG-Kelly机制精神相似的干涉耦合系统的最一般的标量策略有效机制。FAPs之间的竞争市场有很大的潜力为最终用户提供廉价和更好的服务。我们将第二阶段中研究的单个FAP场景扩展为多个FAP竞争由它们服务的Macro用户的场景。此外，我们还研究了一些金融服务提供商组成联盟并共同享受利益的情况。

In order to serve the growing number of wireless devices and their demand for increased data rates, heterogeneous dense wireless networks will be deployed. Due to the coexistence, one challenge is interference. In the final part of the UCIMa project we focus on one instance of a heterogeneous network namely the hybrid access femto cell network. Many operators have launched femtocell service, including Vodafone, SFR, AT&T, Sprint Nextel, Verizon and Mobile TeleSystems. The femtocell access points (FAP), also known as home base station (BS), are connected to the operators' macrocell networks by backhaul digital subscriber line (DSL), optical fiber or other high speed connections.From the theoretical research of the first two phases in the UCIMa project, we will apply the results to the hybrid access framework of femtocell networks. In this phase, the project is intended to fundamentally investigate the economic framework of the hybrid access between the macrocell and the femtocells. The market model for the physical layer resource allocation for the two-tier hybrid access is going to be established.Jamming is a concern in femtocell networks with hybrid access, since the femtocell users and the unregistered macrocell users served by FAP compete for the resources. In addition, the macro users served by the FAP could create jamming to the other macrocell users under MBS without any risk. From the game theoretic point of view, the users have incentives to cheat on their private information, e.g. the channel state information (CSI) for better utilities. We study the problem of jamming and cheating in the hybrid access mode where users migrate freely between MBS and FAP.We extend the framework in phase two to analyze convergence and decentralized learning for the case of wireless network optimization in the presence of adversarial users. The dynamics and convergence properties of an iterative distributed pricing algorithm with malicious users are analyzed. Next, the assumption in phase two that the malicious user has information about the utility function of selfish users is relaxed and the scenario where the malicious user applies a regression-based iterative learning scheme is analyzed. We propose a Bayesian analysis extension to the work carried out in WP3 in phase two taking into account the transmission energy costs of theusers. In addition, we aim to obtain the most general scalar strategy efficient mechanisms for interference coupled systems similar in spirit of VCG-Kelly mechanism.The competitive market among FAPs have a lot of potential to provide cheap and better service for the end users. We extend the single FAP scenario studied in phase two to a scenario where the multiple FAPs compete for the Macro users to be served by them. In addition, we study the case where some of the FAPs form coalitions and jointly enjoy the benefit.