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类型 基础研究 预答辩日期 2018-04-23
开始(开题)日期 2016-09-09 论文结束日期 2018-03-08
地点 李文正楼北512 论文选题来源 国家自然科学基金项目     论文字数 10 (万字)
题目 密集蜂窝网全局无线资源分配分布式算法研究
主题词 分布式算法,多小区,功率控制,资源分配,凸优化
摘要 随着无线传输需求的飞速发展,无线频谱资源日益紧张。在多小区的网络中,小区间采用相同的资源会导致多小区间的干扰。为了解决多小区间的干扰,采用集中式的算法需要交互大量的信息,对于大规模网络来说集中式算法实际操作是不可行的。因此,如何采用分布式的算法来解决多小区的干扰问题是十分有实际意义的。本文围绕如何利用分布式算法来求解多小区干扰问题展开了研究,主要工作如下: 第2章考虑多小区时分复用网络的总功率最小化和总速率最大化的问题,其中小区间干扰导致了小区之间的耦合关系。这种耦合关系以信干燥比耦合模型来体现,以小区负载(小区负载表明小区中资源使用的平均比例)矢量和小区功率矢量为变量进行表征。由于非线性信干燥比耦合模型,多小区时分复用网络的优化问题是非凸性问题。为了解决这些非凸性问题,我们首先考虑单小区网络的优化问题。通过变量变换,优化问题可以等价转化为凸问题。通过求解最优条件,能够获得功率最小化和速率最大化问题的最优闭式解。基于单小区网络优化问题的理论研究结果,设计了一种低复杂度的分布式资源分配和功率控制算法,来用于多小区网络中的总和功率最小化。利用标准干扰函数的性质证明了该算法的收敛性和全局最优性。对于多小区网络中的总和速率优化,提供了一个分布式算法,它可以产生局部最优解。此外,证明了这种分布式算法的收敛性。数值结果说明了理论研究结果,表明了提出的解决方案,相比较传统的均匀功率分配方案具有优越性。 在第3章中,研究了小区间存在相互干扰的下行正交频分复用网络中的功率控制和资源分配问题。这种相互关系的特点是负载耦合模型。小区负载和发射功率通过耦合模型进行交互。考虑三种问题,总和功率最小化,总和速率最大化和总能量效率最大化。针对每个问题,提出了相应分布式的低复杂度功率控制和资源分配算法。 第4章研究了多小区非正交多址接入网络总功率最小化和总速率最大化的问题。考虑到总功率最小化,得到了最优功率分配策略的闭式解,然后成功地将原始问题转化为变量数目更少的线性问题,从而通过使用标准干扰函数来最优地解决。为了解决非凸总速率最大化问题,首先证明单小区的功率分配问题是一个凸问题。通过分析最优条件,单小区中用户的最佳功率分配可以推导出闭合表达式。基于每个小区的最佳解决方案,相应地提出分布式算法以获得有效的解决方案来求解多小区总速率最大化问题。数值结果验证了理论研究结果,显示了提出的解决方案与正交频分多址和广播信道相比的优越性。 第5章通过联合优化负载耦合异构网络中的用户关联,负载分配和功率控制,来解决考虑用户优先级的网络效用最大化问题。为了解决这个非凸性问题,首先通过获得最优资源分配策略的闭合表达式,并得到最优基站负载分配模式。这两个最优结果都被证明对于简化原始问题至关重要,通过指数变换可以将非凸负载分布和功率控制问题转化为等价凸问题。因此,提出一种低复杂度的分布式迭代算法来获得联合优化问题的次优解。仿真结果表明,该算法比传统方法具有更好的性能。
英文题目 RESEARCH ON DISTRIBUTED ALGORITHMS FOR RESOURCE ALLOCATION IN WIRELESS COMMUNICATIONS
英文主题词 Distributed algorithms, multi-cell networks, power control, resource allocation, convex optimization
英文摘要 With the rapid development of wireless transmission requirements, the wireless spectrum resources are becoming more and more limited. Due to frequency reuse among multi-cells, inter-cell interference is introduced inevitably. In order to mitigate the inter-cell interference, the centralized algorithm needs to exchange a large amount of information, which is not feasible for large-scale networks. Therefore, using distributed algorithms to settle the multi-cell interference problem is very practical. This thesis will focus on the distributed algorithm design for multi-cell networks. The main contributions are listed below. Chapter 2 considers the problems of minimizing sum power and maximizing sum rate for multi-cell networks with TDMA, where coupling relation occurs among cells due to inter-cell interference. This coupling relation is characterized by the SINR coupling model with cell load vector and cell power vector as the variables, where cell load measures the average proportion of resource usage in the cell. Due to the nonlinear SINR coupling model, the optimization problems for multi-cell networks with TDMA is nonconvex. To solve these nonconvex problems, we first consider the optimization problems for single-cell networks. Through variable transformation, the optimization problems can be equivalently transformed into convex problems. By solving KKT conditions, the optimal solutions to power minimization and rate maximization problems can be obtained in closed form. Based on the theoretical findings of optimization problems for single-cell networks, we develop a distributed resource allocation and power control algorithm with low complexity for sum power minimization in multi-cell networks. This algorithm is proved to be convergent and globally optimal by using the properties of standard interference function. For sum rate optimization in multi-cell networks, we also provide a distributed algorithm which yields locally optimal solution. Besides, the convergence for this distributed algorithm is proved. Numerical results illustrate the theoretical findings, showing the superiority of our solutions compared to the conventional solution of allocating uniform power for users in the same cell. In Chapter 3, the power control and resource allocation problem is studied in downlink orthogonal frequency division multiplexing networks where mutual interference exists among cells. This mutual relation is characterized by the load coupling model. Both cell load and transmit power interact via the coupling model. We consider three kinds of problems, sum power minimization, sum rate maximization and sum energy efficiency maximization. For each problem, we develop a correspondingly distributed power control and resource allocation algorithm with low complexity. Chapter 4 investigates the problems of sum power minimization and sum rate maximization for multi-cell networks with NOMA. Considering the sum power minimization, we obtain closed-form solutions to the optimal power allocation strategy and then successfully transform the original problem to a linear one with a much smaller size, which can be optimally solved by using the standard interference function. To solve the nonconvex sum rate maximization problem, we first prove that the power allocation problem for a single cell is a convex problem. By analyzing the KKT conditions, the optimal power allocation for users in a single cell is derived in closed form. Based on the optimal solution in each cell, a distributed algorithm is accordingly proposed to acquire efficient solutions. Numerical results verify our theoretical findings showing the superiority of our solutions compared to the orthogonal frequency division multiple access and broadcast channel. Chapter 5 considers the network utility maximization problem with various user priorities via jointly optimizing user association, load distribution and power control in a load-coupled heterogeneous network. In order to tackle the nonconvexity of the problem, we first analyze the problem by obtaining the optimal resource allocation strategy in closed form and characterizing the optimal base station load distribution pattern. Both observations are shown essential in simplifying the original problem and making it possible to transform the nonconvex load distribution and power control problem into convex reformulation via exponential variable transformation. An iterative algorithm with low complexity is accordingly presented to obtain a suboptimal solution to the joint optimization problem. Simulation results show that the proposed algorithm achieves better performance than conventional approaches.
学术讨论
主办单位时间地点报告人报告主题
移动通信国家重点实验室 2017.7.14 中国无线谷 李传锋 量子纠缠网络研究进展
移动通信国家重点实验室 2017.7.10 中国无线谷 林子怀 Distributed Resource allocation and Spectrum Sharing in Future Wireless Cellular Networks
移动通信国家重点实验室 2016.10.17 中国无线谷 Liuqing Yang On Energy-Harvesting Relay Networks: Full-Duplex and Relay Selection
移动通信国家重点实验室 2016.9.28 中国无线谷 Xiaohu Ge Energy Efficiency Optimization of 5G Radio Frequency Chain Systems
陈明老师课题组 2017.12.26 中国无线谷 杨照辉 无线通信资源分配的分布式算法研究
陈明老师课题组 2017.5.15 中国无线谷 杨照辉 Energy Efficient Resource Allocation for Machine-to-machine Communications with NOMA and Energy Harvesting
陈明老师课题组 2016.4.18 中国无线谷 杨照辉 LATEX的排版
陈明老师课题组 2015.4.30 中国无线谷 杨照辉 关于数学在移动通信研究中的作用的讨论
     
学术会议
会议名称时间地点本人报告本人报告题目
IEEE Communications Society 2017.10.12 中国南京 Asynchronous Detection for Machine-to-Machine Systems With Code Division Multiple Access
IEEE Communications Society 2016.4.5 多哈卡塔尔 Cell Planning Based on Minimized Power Consumption for LTE Networks
     
代表作
论文名称
Downlink Resource Allocation and Power Control for D2D Communication Underlaying Cellular Networks
Energy Efficient Non-Orthogonal Multiple Access for Machine-to-Machine Communications
Energy Efficient Resource Allocation in M2M Communications with Multiple Access and EnergyHarvesting
Association and Load Optimization with User Priorities in Load-Coupled Heterogeneous Networks
Joint Time Allocation and Power Control in Multicell Networks With Load Coupling: Energy Saving
On the Optimality of Power Allocation for NOMA Downlinks With Individual QoS Constraints
 
答辩委员会组成信息
姓名职称导师类别工作单位是否主席备注
蔡跃明 正高 教授 博导 解放军理工大学
吴启晖 正高 教授 博导 南京航空航天大学
束锋 正高 教授 博导 南京理工大学
赵春明 正高 教授 博导 东南大学
高西奇 正高 教授 博导 东南大学
      
答辩秘书信息
姓名职称工作单位备注
吴炳洋 副高 副教授 东南大学