基于改进遗传算法的多业务组播系统跨层功率分配方案  

Improved genetic algorithm based cross-layer power allocation scheme in multicast systems with multi-service

作　　者：唐苏文[1] 陈明[1] 

机构地区：[1]东南大学移动通信国家重点实验室,南京210096

出　　处：《东南大学学报（自然科学版）》2009年第2期211-215,共5页Journal of Southeast University：Natural Science Edition

基　　金：国家高技术研究发展计划(863计划)资助项目(2007AA01Z207);东南大学移动通信国家重点实验室研究课题资助项目(2008A06)

摘　　要：结合数据链路层的队列状态信息(QSI)和物理层的信道状态信息(CSI),定义了系统的吞吐量系数和公平性系数,建立组播系统功率分配的离散速率集模型.对遗传算法的初始群体产生、选择、交叉和变异等算子进行改进,形成改进遗传算法;利用改进遗传算法进行动态功率分配和跨层优化.数值仿真结果表明:改进遗传算法能够取得几乎最优的队列时延性能;选取不同的权重对系统吞吐量性能和公平性性能产生重要影响;改进遗传算法获得的系统吞吐量系数和公平性系数在不同场景下较之功率固定分配算法至少提高0.15.A power allocation scheme with multi-service in multicast systems is proposed. From a cross-layer perspective, system throughput coefficient and fairness coefficient are defined taking both queue state information （QSI） in data-link layer and channel state information （CSI） in physical layer into consideration. Then, an optimal power allocation model based on discrete rates is established. The generating of initial population, selecting operator, crossover operator and mutation operator in genetic algorithm are improved to make up an improved genetic algorithm to conduct power allocation. Simulation results show that improved genetic algorithm can obtain almost the best queue delay performance and different weighs influence the system throughput coefficient and fairness coefficient significantly. System throughput coefficient and fairness coefficient obtained by improved genetic algorithm increase more than 0. 15 compared with fixed power allocation algorithm in different simulation scenes.

关 键 词：功率分配 组播系统 跨层优化 改进遗传算法 队列状态信息 信道状态信息 

分 类 号：TN929.5[电子电信—通信与信息系统]