基于LTE-A异构网络中功率控制技术的研究

发布时间：2018-05-16 06:25

本文选题：LTE-A异构网络 + 混合功率模型　；参考：《东华大学》2017年硕士论文

【摘要】：近年来,随着互联网和物联网的飞速发展以及无处不在的移动设备,高速率,低延迟的无线连接的需求出现了前所未有的增长,通信技术面临更加严峻的挑战。异构网络作为一种很有前景的部署方式已经受到多方面的关注。然而,异构网络中不同的接入技术以及不同的网络结构部署带来了更多的干扰问题,因此干扰管理技术是异构网络研究中最为关键的技术之一。首先,根据未来移动通信技术发展面临的挑战,本文通过分析LTE-A异构网络的发展及其关键技术,对干扰管理技术中的功率控制技术进行了深入的研究,使其在不同的网络层中提高通信速率保证用户的服务质量。其次,在对功率控制技术的研究中,本文采用了适用于异构网络并具有高性能自适应调整参数的混合功率控制模型,通过博弈论的方法建模,根据纳什均衡的理论提出了混合功率控制算法。然而纳什均衡的方法并不是最优的,因此基于纳什均衡的改进,提出了分布式混合功率控制算法对功率进行控制,该算法应用斯坦科尔伯格博弈理论,使家庭用户作为博弈的领导者,宏蜂窝用户作为博弈的跟随者,通过对宏蜂窝用户功率消耗定价,提出基于价格和功率的分布式混合功率控制算法。在此算法下,宏蜂窝用户以非合作博弈论的方式最大化自己的效用。本文通过仿真结果表明与纳什均衡对比,斯坦科尔伯格博弈方法能够更快的收敛、发送更少的功率,能够有效的减少干扰,保证相对公平性,更好的保证用户的服务质量。接下来,为了进一步对功率控制技术进行研究,更好的分析纳什均衡和斯坦科尔伯格均衡,本文又引入了博弈论中的帕累托效率的概念,通过对混合功率控制模型和帕累托效率的分析,即在不使任何一个参与者变坏的情况下,也不会使任何参与者的效用变好的帕累托概念中,提出帕累托边界算法,以及纳什均衡性能算法和斯坦科尔伯格性能算法。在最优的条件下形成帕累托边界,并根据纳什均衡性能算法和斯坦科尔伯格性能算法,分别计算了两种算法在帕累托边界下的分布。在帕累托效率的研究中,仿真结果描绘出帕累托边界,以及纳什均衡和斯坦科尔伯格均衡的分布,结果表明斯坦科尔伯格均衡分布在帕累托边界上,是有效的方法,即相对公平、分配最佳、达到最好的结果。最后,本文对整体工作进行了总结与展望,指出了可以完善的方面及进一步研究的方案。
[Abstract]:In recent years, with the rapid development of the Internet of things and ubiquitous mobile devices, high-speed, low-latency wireless connection demand has increased unprecedented, communication technology is facing more serious challenges. As a promising deployment method, heterogeneous networks have attracted much attention. However, different access technologies and different network structures in heterogeneous networks bring more interference problems. Therefore, interference management technology is one of the most important technologies in heterogeneous networks research. Firstly, according to the challenges facing the development of mobile communication technology in the future, this paper analyzes the development of LTE-A heterogeneous network and its key technologies, and makes a deep research on the power control technology in the interference management technology. It can improve the communication rate in different network layers to ensure the quality of service of users. Secondly, in the research of power control technology, the hybrid power control model, which is suitable for heterogeneous networks and with high performance adaptive adjustment parameters, is adopted in this paper, and the model is modeled by the method of game theory. A hybrid power control algorithm is proposed based on Nash equilibrium theory. However, the Nash equilibrium method is not optimal. Therefore, based on the improvement of Nash equilibrium, a distributed hybrid power control algorithm is proposed to control the power. The family user is the leader of the game, and the macro cell user is the follower of the game. By pricing the power consumption of the macro cell user, a distributed hybrid power control algorithm based on price and power is proposed. In this algorithm, macro-cellular users maximize their utility by non-cooperative game theory. The simulation results show that compared with Nash equilibrium, Steinkelberg game method can converge faster, transmit less power, reduce interference effectively, ensure relative fairness, and better guarantee the quality of service of users. Then, in order to further study power control technology and better analyze Nash equilibrium and Steinkelberg equilibrium, this paper introduces the concept of Pareto efficiency in game theory. Based on the analysis of the hybrid power control model and Pareto efficiency, a Pareto boundary algorithm is proposed in the Pareto concept, which does not make any participant worse, nor does it make any participant's utility better. And Nash equalization algorithm and Steinkelberg performance algorithm. The Pareto boundary is formed under the optimal conditions and the distributions of the two algorithms under the Pareto boundary are calculated according to the Nash equalization algorithm and the Steinkerberg performance algorithm. In the study of Pareto efficiency, the simulation results depict the Pareto boundary and the distributions of Nash equilibrium and Steinkelberg equilibrium. The results show that the Stankelberg equilibrium distribution on the Pareto boundary is an effective method. That is, relatively fair, the best distribution, to achieve the best results. Finally, this paper summarizes and prospects the whole work, and points out the aspects that can be perfected and the scheme for further research.
【学位授予单位】：东华大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5

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