文献类型：期刊文献

中文题名：认知无线网络中基于免疫优化的比例公平资源分配

英文题名：Immune-Based Resource Allocation with Proportional Fairness in Cognitive Wireless Network

作者：柴争义[1];刘冉[2];王颖锋[3];朱思峰[4]

第一作者：柴争义

通讯作者：Chai, Z.-Y.

机构：[1]天津工业大学计算机科学与软件学院;[2]华北水利水电学院软件学院;[3]河南财经政法大学计算机与信息工程学院;[4]东南大学移动通信国家重点实验室

第一机构：天津工业大学计算机科学与软件学院,天津300387

年份：2013

卷号：33

期号：8

起止页码：794-800

中文期刊名：北京理工大学学报

外文期刊名：Transactions of Beijing Institute of Technology

收录：CSTPCD;;EI(收录号：20134516948617);Scopus(收录号：2-s2.0-84886733947);北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

基金：国家自然科学基金资助项目(61202099;61171081;61201175;61271207);国家自然基金委-河南省人民政府人才培养联合基金(U1204618);江苏省博士后科研基金资助项目(1202006C);河南省教育厅自然科学研究重点项目(13A520192)

语种：中文

中文关键词：认知无线网络;免疫克隆;OFDM;资源分配;比例公平

外文关键词：cognitive wireless network; immune clone algorithm; orthogonal frequency division multiple; resource allocation; proportional fairness

摘要：针对认知无线网络中基于OFDM技术的资源分配,将其建模为一个约束优化问题,进而提出了一种基于免疫克隆的求解方法.算法采用两阶段资源分配方法,即先将子载波分配给用户,然后基于免疫优化算法给不同的子载波分配功率.此外,算法充分考虑了主用户可容忍的干扰约束及次用户对资源的比例需求,更符合实际要求.根据问题本身特点,设计了适合算法求解的编码、克隆、变异算子.仿真实验结果表明,在总发射功率、误码率及主用户可接受的干扰等约束下,本算法可以获得较高的数据吞吐量,并保证次用户对资源需求的公平性.
The solution of resource allocation of OFDM-based cognitive wireless network could be formulated into an optimization problem with constraints.An immune clonal algorithm is proposed to solve the problem.The resource allocation is divided into two steps.First,the subcarriers are allocated to secondary users.Second,the immune-based algorithm is employed to allocate power for subcarriers.Moreover,the proposed algorithm fully takes into account the interference that primary user can tolerate and the proportional fair demands for secondary users.The suitable operators,such as coding,clonal,mutation,are designed for solving the problem.Experiments results show that,subject to the constraints of total power,BER （bit error rate） and the acceptable interferences of primary user,the proposed algorithm obtains high system throughout with proportional fairness among the secondary users.Both theoretical analysis and simulation results show the effectiveness of the proposed algorithm.