医疗EMI限制下移动网络的功率控制研究

发布时间：2018-10-22 10:08

【摘要】：医疗问题与人们的生活质量密切相关,一直以来都是民生关注的热点。移动医疗,一种以移动计算、医疗传感和通信技术为基础的新型医疗保健模式,通过使用移动通信技术来提供医疗服务。移动医疗的出现给优化医疗资源配置、提高医疗效率与质量、降低就诊成本等带来了有效的解决方法。目前,基于移动医疗的相关研究已越来越被人们所关注。因此本文在移动医疗的背景下讨论功率控制问题。功率控制作为通信系统优化网络资源配置的一项关键技术,可以减少系统内信号的相互干扰,使系统容量最大化。与传统功率控制研究相比,在移动医疗场景下进行功率控制研究其特点和限制条件会有所不同。在移动医疗场景下使用无线通信会存在一个关键问题,信号的辐射会对医疗传感器产生电磁干扰(EMI),且干扰程度随着通信发射功率的提高而增加,高水平的电磁干扰可能导致医疗传感器的严重故障。基于医疗传感器的电磁敏感性,如何进行功率控制,在实现网络资源优化分配的同时也能保证医疗传感器的正常工作,这是本文研究的主要问题。功率控制过程中,由于无线网络中的用户具有自私性,每个用户都倾向于增大功率来最大化自己的性能,但这种功率的增大会对网络中其他用户造成干扰,并且过大的功率会给医疗设备带来有害的EMI。博弈论作为解决利害冲突的数学理论,由于不同场景下的功率控制过程与博弈过程的契合度非常高,所以可以用博弈论的思想来分析功率控制问题。如何运用博弈论来解决上述的矛盾问题是本文研究的关键。本文基于移动医疗背景,以CDMA系统为例,提出两种在非合作博弈论框架下的功率控制算法以调度数据传输。局部功率控制算法,采用基于经典博弈论的联合功率和速率控制方法,目的是最大化受到电磁干扰约束的每个无线用户的网络效用。全局功率控制算法,采用基于最优回报原则的势博弈论的功率控制方法,目的是在最小化电磁干扰的前提下,引导每个用户实现网络级最优化(近似最优)。最后我们对两种算法分别进行仿真实验,数据结果表明,两种算法都能有效地将电磁干扰控制在可接受的范围内。其中我们的局部功率控制算法可以收敛到唯一纳什均衡,可以在应对移动医疗环境变化时实现不错的性能;所提出的全局功率控制算法比现有算法有8%的网络性能增强。
[Abstract]:Medical problems are closely related to people's quality of life and have always been the focus of people's livelihood. Mobile medicine, a new medical care model based on mobile computing, medical sensing and communication technologies, provides medical services through the use of mobile communication technologies. The emergence of mobile medical treatment has brought effective solutions to optimize the allocation of medical resources, improve the efficiency and quality of medical treatment, and reduce the cost of medical treatment. At present, the related research based on mobile medicine has been paid more and more attention. Therefore, this paper discusses the power control problem in the context of mobile medicine. Power control is a key technology in optimizing network resource allocation in communication system. It can reduce the interferences between signals and maximize the capacity of the system. Compared with the traditional power control research, the research on power control in mobile medical settings will have different characteristics and constraints. The use of wireless communication in mobile medical scenarios will have a key problem. The electromagnetic interference (EMI),) caused by the radiation of the signal will increase with the increase of the transmission power of the communication. High levels of electromagnetic interference may lead to serious malfunction of medical sensors. Based on the electromagnetic sensitivity of the medical sensor, how to control the power, realize the optimal allocation of network resources and ensure the normal operation of the medical sensor is the main problem studied in this paper. In the process of power control, due to the selfishness of users in wireless network, each user tends to increase power to maximize their own performance, but this increase of power will interfere with other users in the network. And too much power can bring harmful EMI. to medical devices As a mathematical theory to solve conflicts of interest game theory can be used to analyze the power control problem because of the high consistency between the power control process and the game process in different scenarios. How to use game theory to solve the above-mentioned contradiction is the key of this paper. Based on the background of mobile medicine and taking CDMA system as an example, this paper presents two power control algorithms in the framework of non-cooperative game theory to schedule data transmission. The local power control algorithm uses a combined power and rate control method based on classical game theory to maximize the network utility of each wireless user constrained by EMI. The global power control algorithm adopts the potential game theory based power control method based on the principle of optimal return. The purpose of the algorithm is to guide each user to achieve network-level optimization (approximately optimal) under the premise of minimizing electromagnetic interference (EMI). Finally, the two algorithms are simulated, and the results show that the two algorithms can effectively control the EMI within an acceptable range. Our local power control algorithm can converge to the unique Nash equilibrium and can achieve good performance when dealing with the change of mobile medical environment. The proposed global power control algorithm has 8% better network performance than the existing algorithms.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5

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