干扰约束的认知网络最优功率分配算法  

Optimal power allocation algorithm of interference constrained cognitive network

作　　者：许翊[1] 许晓东[2] XU Yi;XU Xiao dong(Danyang Normal Insititute, Zhenjiang College, Danyang 212300, China;School of Computer, Jiangsu University, Zhenjiang 212000, China)

机构地区：[1]镇江高等专科学校丹阳师范学院,江苏丹阳212300 [2]江苏大学计算机学院,江苏镇江212000

出　　处：《计算机工程与设计》2018年第5期1239-1242,1253,共5页Computer Engineering and Design

基　　金：国家自然科学基金项目(61005017)

摘　　要：为提高认知网络的频谱利用效率和信道数据速率,提出一种基于最大速率和干扰约束的认知网络最优功率分配算法。提出认知中继系统模型,分析用户的发送/接收信号功率及接收信号,即干扰加噪声比;将成功传递位的最大化速率问题转化为凸优化问题,提出最大干扰电平约束与中继功率的线性约束组合方程式,通过使用Karush-Kuhn-Tucker(KKT)条件求得最优功率分配方案。实验结果表明,该算法的信道利用率分别为对比算法的121.3%和118.6%。To improve spectral efficiency and channel data rate of cognitive networks,a cognitive network optimal power allocation algorithm based on maximum rate and interference constraint was proposed.Cognitive relay system model was proposed to analyze the transmission/reception signal power and the received signal,namely interference plus noise ratio.The successful delivery bit rate maximization problem was transferred into a convex optimization.A linear constraint combination equation of maximum interference level constraint and relay power was proposed.Karush-Kuhn-Tucker（KKT）conditions were used to obtain optimal power allocation scheme.Experimental data show that the channel utilization of the algorithm is 121.3% and 118.6% of that of the comparison algorithm respectively.

关 键 词：认知网络 干扰电平约束 功率分配 速率优化 KKT最优化条件 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]