| 摘要: |
| 为了充分实现中继协作，降低多中继协作通信系统功率分配优化问题的计算复杂度，提出了基于萤火虫算法的多中继功率分配方案。在一定的总功率和节点功率约束下，以最大化平均信噪比为优化目标函数，建立了多中继协作系统的功率分配最优化模型。选取该目标函数作为萤火虫的适应度函数，用向量表示萤火虫的状态，该向量的维数为待分配源节点和中继节点的个数，通过萤火虫聚集得到种群中最好的萤火虫，即可获得渐进最优功率分配。仿真结果表明，与平均功率分配相比，基于萤火虫算法的功率分配方案能降低2.44%~6.17%的比特差错率，提高了系统性能。 |
| 关键词: 多中继协作通信 功率分配 萤火虫算法 |
| DOI： |
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| 基金项目:国家自然科学基金资助项目(61263005)；贵州省科学技术基金资助项目（\[2011\]2193号） |
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| Power allocation for multi-relay cooperative systems based on glowworm swarm optimization algorithm |
| TANG Si-teng,LIU Zi-yan,SHUAI Yang |
| () |
| Abstract: |
| To fully realize the potentials of relay-assisted transmission and reduce the computational complexity of power allocation for multi-relay cooperative communication systems,a power allocation scheme based on glowworm swarm optimization(GSO) algorithm is proposed. With a total transmiting power and per-node transmitting power constraints,the power allocation optimization model is presented to maximize the average signal-to-noise ratio(SNR). The objective function is selected as fitness function of GSO,status of fireflies is measured by a vector,of which each element represents power of source node and the relay node,respectively. Most fireflies in the GSO gather at the location where the fitness function value is the best,i.e. asymptotically optimal power allocation scheme is obtained. Simulation and numerical results demonstrate that power allocation scheme based on GSO achieves better performance with lower bit error rate up to 2.44%~6.17% compared with equal power allocation(EPA). |
| Key words: multi-relay cooperative communication power allocation glowworm swarm optimization |
《电讯技术》编辑部 