基于博弈论的认知无线网络频谱共享方法研究

发布时间:2018-07-31 07:32
【摘要】:认知无线电技术能有效提高无线频谱资源利用率,是解决无线频谱供需矛盾的有效方法之一。无线频谱资源共享主要涉及频谱分配、信道配置、功率控制和噪声容限等几个方面。基于博弈论的认知无线网络频谱共享是针对在频谱资源供需不均衡、信道特性随机变化的条件下,采用经济手段动态配置频谱资源,在保证授权用户正常通信的前提下,使认知用户也能共享频谱,从而提高频谱资源的利用率。传统无线频谱资源配置方式的网络容量因固定的频谱数量而保持相对稳定;而在认知无线网络中,由于认知用户可以机会地接入授权用户的频谱资源,同时授权用户对频谱资源的使用也具有随机动态变化的特性,导致认知用户对频谱资源的使用也呈现随机时变性,使得认知网络的频谱资源管理难度明显增加。因此如何对认知无线网络的频谱资源进行有效管理,提高服务质量和网络性能,已成为目前相关领域的研究热点。本论文主要采用博弈论算法,围绕认知网络频谱资源共享策略与方法进行研究,涉及到用户接入、频谱分配、服务质量、功率控制等关键技术,主要研究内容和创新成果如下:1)研究了基于衬底式(underlay)共享方式的认知无线网络功率控制方法,提出一种联合服务质量、功率控制、噪声容限和干扰抑制的分布式非合作功率控制算法;围绕频谱资源共享问题,采用博弈理论分析授权用户控制干扰容限,认知用户分布式非合作博弈竞争的模型,推导证明其纳什均衡解的存在性和唯一性。与传统算法相比较,该方法在获得相似通信质量的条件下能进一步降低认知用户的发射功率,降低能源消耗,具有收敛快、误差小的优点。2)利用微观经济学理论的管理方法,基于经济效益最大化模型,研究了认知无线网络的功率控制、接入数量、信道质量、远近距离和经济效益的关系,提高认知网络的公平性和经济效益。由于普通的分布式功率控制算法存在授权用户没有获利、参与积极性不高等缺点,我们提出一种干扰权限价格算法,引入干扰权限和功率价格来控制认知用户的接入数目和发射功率,调整认知用户与授权用户的距离、信道质量、接入数目和功率大小等因素。文中采用一种更为公平的基于干扰定价的非合作分布式功率分配算法,该算法使用价格杠杆来调节授权和认知用户之间的功率分配,限制认知用户贪婪增大发射功率,同时激发授权用户分享更多频谱资源以获取更多经济利益的积极性。与传统算法相比较,此算法更具现实意义和应用价值。3)对于认知无线网络,用户效益最大化是协作通信的主要目标之一。为此,本文提出一种以用户联盟为单位的共享机制,用户联盟内以衬底式(underlay)共享频谱,用户联盟间以覆盖式(overlay)复用物理信道的联盟博弈控制策略。提出一种基于联盟博弈的配对算法,根据网络状况动态选择协作对象,以用户间的偏好值大小决定首选次序的先后,综合考虑网络吞吐量和认知用户的联盟利益。将配对问题建模成博弈配对模型,研究配对的稳定性,证明稳定配对解满足Pareto最优准则。对比分析了随机、稳定配对算法的性能,仿真结果均证明此策略比随机配对算法有较大改进,达到更大的系统容量且其公平性更好。
[Abstract]:Cognitive radio technology can effectively improve the utilization of radio spectrum resources. It is one of the effective methods to solve the contradiction between the supply and demand of the wireless spectrum. The wireless spectrum resource sharing mainly involves spectrum allocation, channel configuration, power control and noise tolerance. The spectrum sharing based on game theory is aimed at the supply of spectrum resources. Under the condition of unbalance and random variation of channel characteristics, the frequency spectrum resources can be dynamically configured by economic means. In order to ensure the normal communication of the authorized users, the cognitive users can share the spectrum and improve the utilization of the spectrum resources. The network capacity of the traditional wireless spectrum resource configuration is maintained by the fixed spectrum number. In the cognitive wireless network, in the cognitive wireless network, the cognitive users can access the spectrum resources of the authorized users, while authorizing the users to use the spectrum resources also has the characteristics of random dynamic changes, which leads to the random time variation of the use of the spectrum resources by the cognitive users, which makes the spectrum resource management of the cognitive network difficult. Therefore, how to effectively manage the spectrum resources of cognitive wireless network and improve the quality of service and network performance has become a hot topic in the related fields. This paper mainly uses game theory algorithm to study the strategies and methods of spectrum resource sharing in cognitive network, involving user access, spectrum allocation and service quality. Key technologies, such as quantity, power control, and other key technologies, the main research content and innovation results are as follows: 1) the cognitive wireless network power control method based on the underlay sharing mode is studied, and a distributed non cooperative power control algorithm for the quality of service, power control, noise tolerance and interference suppression is proposed. The game theory is used to analyze the authorization user to control the interference tolerance and the model of the distributed non cooperative game competition of the user. The existence and uniqueness of the Nash equilibrium solution are derived. Compared with the traditional algorithm, the method can reduce the power of the users and reduce the energy of the cognitive users. Using the management method of microeconomic theory and based on the model of economic benefit maximization, we study the relationship between the power control, the number of access, the quality of the channel, the distance and the economic benefit of the cognitive wireless network, and improve the fairness and economic benefit of the recognition network, because of the common distribution,.2. The power control algorithm has the disadvantage that the authorized user is not profitable and participates in high enthusiasm. We propose a interference privilege price algorithm, which introduces the interference rights and power prices to control the number of access and transmit power of the cognitive users, and adjusts the distance between the cognitive users and the authorized users, the channel quality, the number of access and the size of the power and so on. In this paper, a more equitable non cooperative distributed power allocation algorithm based on interference pricing is used. This algorithm uses price lever to regulate power allocation between authorized and cognitive users, restrict the greed and transmit power of cognitive users, and stimulate the authorized users to share more spectrum resources to obtain more economic benefits. Polarity. Compared with the traditional algorithm, this algorithm has more practical significance and application value.3). For cognitive wireless networks, the maximum user benefit is one of the main objectives of cooperative communication. For this reason, this paper proposes a sharing mechanism based on user alliance, shared spectrum of underlay in the user alliance, and overlay between user alliances. Overlay reuses the alliance game control strategy of the physical channel. A matching algorithm based on alliance game is proposed. The cooperative object is dynamically selected according to the network condition, the preference order of the user is determined by the preference value between users, and the network throughput and the alliance interests of the users are considered synthetically. The matching problem is modeled as a game pairing. The stability of pairing is studied, and the stable pairing solution satisfies the Pareto optimal criterion. The performance of the stochastic and stable pairing algorithm is compared and analyzed. The simulation results show that the strategy is better than the random pairing algorithm to achieve greater system capacity and its fairness is better.
【学位授予单位】:华南理工大学
【学位级别】:博士
【学位授予年份】:2016
【分类号】:TN925

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相关期刊论文 前1条

1 姜永;陈山枝;胡博;;异构无线网络中基于Stackelberg博弈的分布式定价和资源分配算法[J];通信学报;2013年01期



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