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蜂窝网络下基于max-min公平性的D2D功率分配
引用本文:尼俊红,申振涛,杨会峰.蜂窝网络下基于max-min公平性的D2D功率分配[J].计算机应用,2017,37(4):945-947.
作者姓名:尼俊红  申振涛  杨会峰
作者单位:1. 华北电力大学 电子与通信工程系, 河北 保定 071003;2. 国网河北省电力公司 信息通信分公司, 石家庄 050021
基金项目:国家自然科学基金资助项目(61302106)。
摘    要:针对多个终端直通通信(D2D)用户共享多个蜂窝用户资源的公平性问题,在保证蜂窝用户速率的前提下,提出了基于最大最小公平性(max-min fairness)的功率分配算法。该算法首先将非凸优化问题转化为含凸函数的差(DC)规划问题,然后采用凸近似的全局优化算法和对分算法对D2D实现功率优化。仿真结果表明,与只采用凸近似的全局优化算法相比,所提算法收敛性更优,同时最大化了瓶颈用户的速率。

关 键 词:终端直通通信  最大最小公平性  凸函数的差规划  功率优化  
收稿时间:2016-08-30
修稿时间:2016-12-25

D2D power allocation based on max-min fairness underlying cellular systems
NI Junhong,SHEN Zhentao,YANG Huifeng.D2D power allocation based on max-min fairness underlying cellular systems[J].journal of Computer Applications,2017,37(4):945-947.
Authors:NI Junhong  SHEN Zhentao  YANG Huifeng
Affiliation:1. Department of Electronics and Communication Engineering, North China Electric Power University, Baoding Hebei 071003, China;2. Information and Communication Branch, State Grid Hebei Electric Power Company, Shijiazhuang Hebei 050021, China
Abstract:Concerning the fairness problem of multiple Device-to-Device (D2D) users reusing the spectrum resources allocated to cellular subscribers, a power allocation algorithm based on max-min fairness was proposed under the premise of guaranteeing the rate of cellular users. First, the nonconvex optimization problem was transformed into a Difference between Convex functions (DC) programming problem, then the global optimization algorithm of convex approximation and the bisection algorithm were used to achieve power optimization of D2D. Simulation results show that compared with the global optimization algorithm which only uses convex approximation, the proposed algorithm has better convergence and maximizes the bottleneck rate of D2D users.
Keywords:Device-to-Device (D2D)                                                                                                                        max-min fairness                                                                                                                        difference between convex functions programming                                                                                                                        power optimization
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