基于多维离散粒子群优化的协同OFDMA系统跨层资源分配  

Multi-values discrete particle swarm optimization for cross layer resource allocation in cooperative OFDMA systems

作　　者：孥为[1] 熊春林[1] 王德刚[1] 张晓瀛[1] 魏急波[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院,湖南长沙410073

出　　处：《通信学报》2014年第4期17-24,共8页Journal on Communications

基　　金：国家自然科学基金资助项目(61101096,61002032,61372098,61372099,61302140,91338105);湖南省自然科学基金资助项目(11jj4055)~~

摘　　要：针对多服务情况下协同OFDMA(orthogonal frequency division multiple access)系统的资源分配问题,在基站和中继单独功率约束条件下,以最大化用户的效用(utility)总和为目标,提出了一种基于多维离散粒子群(MDPSO)的渐进最优资源分配算法。该算法采用多值离散变量来编码粒子位置,并针对多维离散空间构建了新的基于概率信息的粒子速度和位置更新算法,且引入变异操作来克服粒子群算法的早熟问题。此外,还采用了迭代注水法进行最优功率分配。仿真结果表明,所提算法在总效用、吞吐量和公平性上均明显优于已有资源分配算法。The resource allocation problem in cooperative OFDMA systems with mobile stations （MS） on multi-services was investigated. In order to maximize the sum utility of all MS under per-relay power constraint（PPC）, an asymptotic optimal resource allocation algorithm based on multi-values discrete particle swarm optimization （MDPSO） was pro-posed. Unlike the traditional discrete particle swarm optimization （DPSO） algorithm, the proposed one denotes the parti-cle position by discrete multi-value variable. Furthermore, new probability based operations for computing particle veloc-ity and updating particle positions were developed, and the mutation of particle positions was also introduced to over-come the premature convergence problem. The proposed MDPSO can also be applied widely to solve the combinatorial optimization problems （COP）. Furthermore, iterative waterfilling was used to complete power allocation. Simulation re-sults show that the proposed method achieves higher sum utility of all MSs and higher degree of user fairness than the existing methods.

关 键 词：资源分配 离散粒子群优化 效用函数 

分 类 号：TN911[电子电信—通信与信息系统]