[1]胡 敏,朱 琦.基于微分博弈的群智频谱感知算法[J].计算机技术与发展,2021,31(03):138-143.[doi:10. 3969 / j. issn. 1673-629X. 2021. 03. 024]
　HU Min,ZHU Qi.Spectrum Crowd-sensing Algorithm Based on Differential Games[J].,2021,31(03):138-143.[doi:10. 3969 / j. issn. 1673-629X. 2021. 03. 024]
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基于微分博弈的群智频谱感知算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
31
期数:
2021年03期
页码:
138-143
栏目:
网络与安全
出版日期:
2021-03-10

文章信息/Info

Title:
Spectrum Crowd-sensing Algorithm Based on Differential Games
文章编号:
1673-629X(2021)03-0138-06
作者:
胡 敏; 朱 琦
南京邮电大学 通信与信息工程学院,江苏 南京 210003
Author(s):
HU Min; ZHU Qi
School of Telecommunications & Information Engineering,Nanjing University of Posts and Telecommunications, Nanjing 210003,China
关键词:
计算机通信技术; 频谱感知; 检测概率; 群智感知; 微分博弈; 纳什均衡
Keywords:
computer communication technology; spectrum sensing; detection probability; crowd-sensing; differential game; Nash equilibrium
分类号:
TN929. 5
DOI:
10. 3969 / j. issn. 1673-629X. 2021. 03. 024
摘要:
计算机技术和通信技术的融合是一个必然的趋势,频谱感知作为计算机通信技术的一个组成部分,是解决现有无线系统频谱利用率低的关键技术之一。 将群智感知与频谱感知相结合,提出了一种基于微分博弈的群智频谱感知算法。平台的效用定义为第三方支付的报酬减去付给次用户的报酬,次用户的效用定义为平台支付的报酬减去次用户参与频谱感知任务的成本,以各自效用最大为目标设计了一种非合作的微分博弈模型。 该微分博弈模型包含一个微分方程、平台效用和次用户效用,通过公式推导求解其反馈纳什均衡,得到平台和用户的最优策略的表达式,即平台决定任务的最优价格,各个次用户确定频谱的最优检测概率(即感知时间)。 仿真结果表明,平台和次用户采取最优策略时效用高于采取固定策略时的效用。
Abstract:
The convergence of computer technology and communication technology is an inevitable trend. As a comp-onent of computer communication technology,spectrum sensing is one of the key technologies to solve the inefficient spectrum utilization rate of existing wireless systems. Combined crowd-sensing with spectrum sensing,we propose a spectrum crowd-sensing algorithm based on differential games. A non-cooperative differential game model is designed,where the utility of the platform is defined as the compensation paid by the third party minus the compensation paid to the secondary user,and the utility of the secondary users are defined as the compensation paid by the platform minus the cost of the secondary users爷 participation in the sensing task to maximize their respective utility. The differential game model contains a differential equation, the utility of the platform and the utility of the secondary users. The expression of the optimal strategy of the platform and users are obtained by solving the feedback Nash equilibrium by formula derivation,where the platform determines the optimal price of the task,and each user determines the optimal detection probability (sensing time). Simulation results show that the utility of the platform and users adopting the optimal strategy is higher than that of fixed strategy.

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更新日期/Last Update: 2020-03-10