认知小蜂窝网络中基于干扰温度限制的下行能效资源分配算法

发布时间：2018-04-21 22:28

本文选题：认知小蜂窝网络 + 能量效率　；参考：《电子学报》2017年04期

【摘要】：为最大化认知小蜂窝基站的能量效率,本文基于博弈论模型分析了下行联合频谱资源块和功率分配行为.在干扰受限环境下,多个基站采用分布式结构共享空闲频谱资源.为避免累加干扰损害主用户的通信,算法中引入了功率和干扰温度限制.由于具有耦合限制的分数形式的能量效用函数是非凸最优的,通过将其转化为等价的减数形式进行迭代求解.给定频谱资源块分配策略后,主博弈模型可被重新建模为便于求解发射功率的等价子博弈模型,并通过代价的形势解除耦合限制.仿真结果表明,本文所提算法能够收敛到纳什均衡,并有效提高了系统资源利用率和能量效率.
[Abstract]:In order to maximize the energy efficiency of cognitive small cellular base stations, this paper analyzes the joint downlink spectrum block and power allocation behavior based on game theory model. In the interference-limited environment, multiple base stations share free spectrum resources with distributed structure. In order to avoid the cumulative interference harming the communication of the primary user, the power and interference temperature limits are introduced in the algorithm. Since the energy utility function in fractional form with coupling constraints is nonconvex, it is solved iteratively by transforming it into equivalent subtraction. Given a spectrum resource block allocation strategy, the main game model can be remodeled as an equivalent sub-game model for solving the transmit power, and the coupling constraints can be lifted by the situation of the cost. Simulation results show that the proposed algorithm can converge to Nash equilibrium and effectively improve the system resource utilization and energy efficiency.
【作者单位】：大连海事大学信息科学技术学院;杭州电子科技大学浙江省数据存储传输及应用技术研究重点实验室;
【基金】：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) 浙江省数据存储传输及应用技术研究重点实验室(杭州电子科技大学)开放基金(No.201401)
【分类号】：TN929.5

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