超密集异构网络中无线资源管理关键问题的研究

发布时间：2018-04-13 01:27

本文选题：Small + cell　；参考：《北京交通大学》2017年硕士论文

【摘要】：当今的世界处在无处不在的大连接时代,下一代移动通信网络(5G)的容量和覆盖范围将不断增加,以支持不断增加的数据流量、终端设备,提供高可靠性的无缝连接和高速率的数据传输。为了满足5G的容量和覆盖需求,超密集网络(Ultra Dense Network,UDN)是必不可少的一项关键技术。超密集网络的前身是异构 Small cell 网络(Heterogeneous Small cell Network),Small cell 网络节点具有发射功率低,部署灵活,以及易于配置和运营成本低等优点。但UDN部署带来容量和覆盖提升的同时,也给无线资源管理工作带来了挑战。例如用户的小区选择问题,小区间干扰严重问题,Small cell系统性能如何进一步提升问题。5G还提出"绿色通信"的要求,所以超密集网络部署需要降低能耗,提高频谱效率。本论文针对超密集异构Small cell网络的用户小区选择问题、能量效率和频谱效率优化问题进行了研究。首先针对Femtocell小区选择问题,提出了基于非合作买卖博弈小区选择的方法;其次,针对Picocell系统能效-谱效联合优化问题,提出了使用NSGA-2算法求解该多目标问题,进行无线资源分配的方案。本论文的主要研究内容以及创新点如下:1.本论文提出了基于非合作买卖博弈的分布式小区选择方案。以用户为买方,以Femtocell为卖方,建立了非合作买卖模型。根据用户接入前后的信干噪比设计了 Femtocell的奖励函数,又根据奖励函数为买卖双方设计了效用函数。为了使用户在获得速率和付出代价之间做一个权衡,又为用户的效用函数设置了权重因子。为了解决Femtocell快速完成对待接入用户的报价问题,提出了一种价格更新算法。该博弈方案是基于信干噪比的,保障用户获得更好的服务质量,还为Femtocell增加收益,仿真结果验证了该算法的良好性能。2.本论文将问题建模为一个Picocell系统能效-谱效多目标优化问题,而不是传统的只限于单一的优化容量、谱效或能效的单目标问题。该优化问题为Marco cell用户设置了最低的资源块信干噪比门限,又为Picocell用户设置了最低的传输速率,同时保障了 Marco cell用户和Picocell用户的服务质量(QoS)。仿真结果表明了这两个约束条件对用户QoS的保障。3.不同于传统的权重系数法,本论文使用了 NSGA-2算法解决能效-谱效多目标优化问题。NSGA-2算法同时进行资源块和发射功率分配,避免了一般分步求解无法保证最优解的问题。仿真结果表明,本论文的NSGA-2算法性能优于权重系数法。
[Abstract]:Today's world is in the ubiquitous era of large connectivity, and the capacity and coverage of the next generation mobile communication network (5G) will continue to increase to support increasing data traffic, terminal equipment,Provide high reliability seamless connection and high rate data transmission.In order to meet the requirement of 5G capacity and coverage, Ultra Dense Network (UDN) is an essential key technology.The precursor of ultra-dense network is heterogeneous Small cell network small cell network node, which has the advantages of low transmit power, flexible deployment, easy configuration and low operating cost.However, while UDN deployment brings about higher capacity and coverage, it also brings challenges to wireless resource management.For example, the problem of cell selection for users, the serious problem of intercellular interference, and how to further improve the performance of small cell system. 5G also puts forward the requirement of "green communication". Therefore, the deployment of super-dense networks needs to reduce energy consumption and improve spectral efficiency.In this paper, the problem of cell selection, energy efficiency and spectrum efficiency optimization for ultra-dense heterogeneous Small cell networks is studied.For the problem of Femtocell cell selection, a method of cell selection based on non-cooperative buying and selling game is proposed. Secondly, aiming at the problem of joint optimization of energy efficiency and spectrum effect in Picocell system, a NSGA-2 algorithm is proposed to solve the multi-objective problem.A scheme for allocating wireless resources.The main contents and innovations of this thesis are as follows: 1.In this paper, a distributed cell selection scheme based on non-cooperative trading game is proposed.Taking the user as the buyer and Femtocell as the seller, the non-cooperative trading model is established.According to the signal-to-noise ratio before and after the user access, the reward function of Femtocell is designed, and the utility function is designed for both the buyer and the seller according to the reward function.In order to make the user make a trade-off between the acquisition rate and the cost, a weighting factor is set for the utility function of the user.In order to solve the problem of quick completion of Femtocell bidding for access users, a price updating algorithm is proposed.The game scheme is based on signal-to-noise ratio to ensure better quality of service for users and increase revenue for Femtocell. The simulation results show that the algorithm has good performance. 2.In this paper, the problem is modeled as a multi-objective optimization problem of energy efficiency and spectral efficiency in Picocell systems, rather than a single objective problem which is limited to a single optimization capacity, spectral effect or energy efficiency.The optimization problem sets the minimum resource block signal-to-noise ratio threshold for Marco cell users, sets the minimum transmission rate for Picocell users, and guarantees the QoS of Marco cell users and Picocell users.The simulation results show that these two constraints guarantee the user QoS. 3. 3.Different from the traditional weight coefficient method, the NSGA-2 algorithm is used to solve the energy-efficiency and spectral efficiency multi-objective optimization problem. NSGA-2 algorithm is used to allocate the resource block and transmit power at the same time, thus avoiding the problem that the general step-by-step solution can not guarantee the optimal solution.The simulation results show that the performance of the NSGA-2 algorithm is better than that of the weight coefficient method.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5

【参考文献】