| 摘要: |
| 在认知无线电中，由于次用户干扰门限要求的存在，传统频谱功率分配方式获得的次用户有效信道容量较低。针对这一问题，提出了一种基于粒子群算法的频谱功率分配算法。首先建立基于干扰距离的认知网络干扰模型，将频谱功率分配问题转化为函数优化问题，并借助混合随机变异思想的粒子群算法进行求解；针对寻优过程中的约束问题，提出了一种基于投入产出比的外点法，保证粒子群在可行域中寻优，最终获得频谱功率分配。仿真结果表明，与传统算法相比，所提算法能够获得较高的次用户有效信道容量。 |
| 关键词: 认知无线电 信道容量 频谱功率分配 粒子群优化 外点法 |
| DOI： |
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| 基金项目: |
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| Application of improved particle swarm optimization in power and spectrum allocation |
| SUN Peiran,WANG Keren,FENG Hui |
| () |
| Abstract: |
| In cognitive radio,the effective channel capacity of secondary users is low when their interference threshold is required.To solve this problem,a power and spectrum allocation algorithm is proposed which is based on particle swarm optimization(PSO) algorithm.Firstly,an optimal model of maximizing channel capacity based on the interference distance is established in the cognitive network.As a result,the problem of power and spectrum allocation can be transformed into a function optimization.Secondly,the new algorithm combining the random mutation algorithm with PSO algorithm is used to solve the optimal solution of the function.Whereas,the proposed algorithm is easy to fall into a local optimum.To ensure the particle swarm searching in a feasible region,an external point method based on input-output ratio is proposed in the process of optimization.Finally,a preferable power allocation is obtained.Simulation results show that the proposed algorithm can obtain higher effective channel capacity of secondary users compared with traditional algorithms. |
| Key words: cognitive network channel capacity power and spectrum allocation particle swarm optimization external point method |
《电讯技术》编辑部 