摘要: |
高峰均比(PAPR)是多载波码分多址(MCCDMA)技术应用中亟待解决的关键问题。对于采用Wa
lshHadamard(WH)
扩频码的系统来说,优化用户扩频码的分配方案可降低系统的PAPR,但最优扩频码分配方法
运算复杂度太高。为此,采用具有优良迭代寻优能力的粒子群优化算法(PSO)来降低算法
的复杂度。改进算法将最优分配方案的高维搜索问题转化为粒子群迭代寻优过程。分析比较
和仿真结果表明,与最优算法相比,改进算法在降低PAPR性能方面有05~1.5 dB的性
能损失,而复杂度远小于最优算法,是一种简单实用的峰均比降低方法。 |
关键词: 多载波码分多址 扩频码分配 峰均比 粒子群优化算法 |
DOI: |
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基金项目: |
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PSO-based spreading code allocation for PAPR reduction of MC-CDMA signal |
HU Mao-kai,CHEN Xi-hong,XUE Lun-sheng,HUANG Rong-hua |
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Abstract: |
The high peaktoaverage power ratio(PAPR) of Multicarrier Code Division Mult
iple Access(MCCDMA) is a key factor to be solved. In MCCDMA system us
ing WalshHadamard(WH) spreading codes, the spreading code allocation is relate
d to the PAPR and a reasonable allocation strategy can reduce signal PAPR. To reduce the high com
plexity of the optimal allocation method, particle swarm optimization(PSO) is in
troduced for seeking the optimum code allocation. Analysis and simulation results sho
w that the proposed suboptimal method has a small performance loss (0.5~1.5
dB) in reducing PAPR. But the suboptimal method also has very low computational complexity and is suitable for practical system. |
Key words: MC CDMA spread code allocation PAPR particle swarm optimization(PSO) |