电子学报 ›› 2015, Vol. 43 ›› Issue (10): 1911-1917.DOI: 10.3969/j.issn.0372-2112.2015.10.005

• 学术论文 • 上一篇    下一篇

博弈论框架下认知小蜂窝网络的动态资源分配算法

贾亚男, 岳殿武   

  1. 大连海事大学信息科学技术学院, 辽宁大连 116026
  • 收稿日期:2014-04-23 修回日期:2014-07-29 出版日期:2015-10-25 发布日期:2015-10-25
  • 作者简介:贾亚男 男,1986年出生于河南商丘.大连海事大学博士生,主要研究方向为小蜂窝网络、认知无线电、最优化理论和博弈论等.E-mail:jiayanan666@163.com;岳殿武 男,1965年出生于吉林四平.大连海事大学教授,博士生导师,主要研究方向为MIMO无线通信、协作通信、认知无线电和纠错编码等.E-mail:dianwuyue@yahoo.com
  • 基金资助:

    国家自然科学基金(No.61371091,No.61301228);高等学校博士学科点专项科研基金(No.20132125110006);中央高校基本科研业务费专项基金;大连海事大学优秀科技创新团队培育计划(No.3132013334)

Dynamic Resource Allocation Algorithm Based on Game Theory in Cognitive Small Cell Networks

JIA Ya-nan, YUE Dian-wu   

  1. College of Information Science & Technology, Dalian Maritime University, Dalian, Liaoning 116026, China
  • Received:2014-04-23 Revised:2014-07-29 Online:2015-10-25 Published:2015-10-25

摘要:

为提高认知小蜂窝网络(CSCN)的系统容量,本文基于博弈论框架分析了上行链路中频谱、小蜂窝基站和功率的动态分配行为.传统的频谱分配方案只考虑了异质网路中相互独立频带间的最优分配,而没有考虑可重叠频段间的分配模式和上行链路资源的联合优化.基于此,本文提出了一种具有频带可交叉特性的联合分配模型.通过引入干扰温度限制、全新的干扰算子和记忆因子构造了一种新型的上行注水功率算法.仿真结果表明,基于博弈理论的动态选择特性和干扰温度的干扰避免准则,本算法可以有效提高CSCN的吞吐量和鲁棒性.

关键词: 认知小蜂窝网络(CSCN), 博弈论, 频谱分配, 功率分配, 纳什均衡

Abstract:

In order to improve the capacity of the cognitive small cell network (CSCN), this paper analyzed the dynamic allocation of the spectrum, small cell base stations (SBS) and transmission power in the uplink based on the game theory.The traditional allocation scheme only considered the optimal allocation among independent frequency bands in heterogeneous networks, without taking into account the mutually overlapped frequency bands and the joint resource allocation in the uplink.For this reason, the joint optimal allocation etiquette is proposed.The interference temperature constraints, the new interference operator and the memory factor were introduced in the new uplink water-filling algorithm.Based on the characteristic of dynamic selection and the interference avoidance rule of interference temperature.Simulation results show that our algorithm can effectively improve the throughput and robustness of the CSCN.

Key words: cognitive small cell networks (CSCN), game theory, spectrum allocation, power allocation, Nash equilibrium

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