【作者】 高雪；

【导师】 杨清海；

【作者基本信息】 西安电子科技大学 ， 通信与信息系统， 2013， 硕士

【摘要】 在无线网络中，用户间合作技术可以提高网络性能，但分布式的公平合作方案设计仍然是个挑战。本文主要研究基于联盟博弈的资源分配和多业务调度问题，并对其进行了性能分析和仿真验证。首先，研究了无线网络多用户合作模型。用户在不损害其它用户利益并考虑合作功率花销的前提下，采用简单的分布式算法，自组织形成独立并且互不相交的联盟，最大化用户传输速率。然后，研究了联盟框架下具有反馈机制的多用户异构业务资源分配和调度问题。联盟分割有效地适应了用户的信道状态信息(CSI)和队列状态信息(QSI)的动态变化，优化了网络拓扑结构。相比于非合作情况，提出的策略在系统吞吐量和业务时延性能上表现出明显优势。最后，研究了面向智能电网的两阶段多业务调度问题，使簇头节点与多媒体传感器形成联盟，每个联盟的簇头节点采用在线学习算法决策最终的资源分配方案。OPNET下的仿真结果表明，该机制在满足各种业务的QoS要求条件下，实现了能量有效地调度传输。更多还原

【Abstract】 In the wireless network, the network performance can be improved throughcooperation techniques among the users. However, performing a distributed and faircooperation constitutes a major challenge. This thesis aims to solve the problem ofresource allocation and multi-service scheduling scheme by coalitional game theory,and does the performance analysis and simulation validation.Firstly, we model the multi-user cooperation in wireless networks. A simple anddistributed algorithm is constructed to enable the users to self-organize into independentdisjoint coalitions and to allow them to maximize their utilities in terms of rate whileaccounting for the cost of cooperation in terms of power.Afterwards, we consider the problem of resource allocation and traffic schedulingfor the multi-user and multi-service with the aid of the coalition formation game, whichenables the users to autonomically form disjoint coalitions in accordance with thedynamics of channel state information (CSI) and queue state information (QSI).Comparing with the non-cooperative techniques, our proposed scheme achieves betterperformance in terms of both the system throughput and the traffic-delay for theheterogeneous applications.Finally, we study the two-phase multi-service scheduling scheme for smart grids,in which the sink nodes and multimedia sensors form coalition groups, and sink node inevery coalition adopts the online-learning algorithm for the decision that which sinknode gets the transmission token. Simulation by OPNET shows that the schemeachieves energy-efficient scheduling under QoS requirements for multi-traffic.更多还原