| 摘要: |
| 盲均衡可以看作代价函数优化问题。为了改进经典常模算法的性能,研究了利用实数编码遗传算法的常模盲均衡,把均衡器系数向量作为遗传算法的决策变量,采用轮盘赌选择和精英保留策略相结合的混合选择算子、算术交叉算子和非均匀变异方式,经过一系列的遗传操作,搜索到适应度值最高的个体,即均衡器的最优系数。计算机仿真结果证明了算法具有收敛速率快、能够搜索到全局最优解等特点。 |
| 关键词: 遗传算法,盲均衡,实数编码,常模算法 |
| DOI： |
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| 基金项目:国家部级科研项目 |
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| Constant Modulus Blind Equalization Based on Real Coded Genetic Algorithm |
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| Abstract: |
| The blind equalization can be seen as an optimization task of cost function.A new constant modulus blind equalization using a real coded genetic algorithm(GA) is presented for improving the performance of the standard constant modulus algorithm(CMA).The coefficient vector of a blind equalizer is regarded as the decision variables,and the optimal solutions can be obtained by hybrid selection operator of roulette wheel method and elitist model,arithmetic crossover and non-uniform mutation.Computer simulations show that the proposed algorithm has the advantage of fast convergence and the capability of reaching globally optimal solutions. |
| Key words: genetic algorithm(GA),blind equalization,real coding,constant modulus algorithm(CMA) |
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