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Joint channel estimation and multi-user detection for MC-CDMA system using genetic algorithm and simulated annealing

机译:基于遗传算法和模拟退火的MC-CDMA系统联合信道估计和多用户检测

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In multi-carrier code-division multiple-access (MC-CDMA) system the multiple access interference (MAI) is a critical factor that significantly degrades system performance. In this research the genetic algorithm (GA) is employed for joint channel estimation and multi-user detection. For improving exploration and exploitation strengths of GA, a GA-based approach called SAM-GA is developed by incorporating the simulated annealing (SA) to mutation operation. Furthermore, a threshold-based mutation is proposed to refine the SAM-GA scheme. The resulting scheme is called modified SAM-GA for simplicity. Experimental result demonstrates that the proposed modified SAM-GA scheme achieves the best performance in terms of mean squared error (MSE), bit error rate (BER), and convergence rate for joint CIR estimation and multi-user detection in the MC-CDMA system as compared to other schemes.
机译:在多载波码分多址(MC-CDMA)系统中,多址干扰(MAI)是严重降低系统性能的关键因素。在这项研究中,遗传算法(GA)用于联合通道估计和多用户检测。为了提高遗传资源的勘探和开发实力,通过将模拟退火(SA)结合到变异操作中,开发了一种基于遗传的方法,称为SAM-GA。此外,提出了基于阈值的突变以完善SAM-GA方案。为了简单起见,将所得方案称为修改的SAM-GA。实验结果表明,针对MC-CDMA系统中联合CIR估计和多用户检测,提出的改进SAM-GA方案在均方误差(MSE),误码率(BER)和收敛率方面达到了最佳性能。与其他方案相比

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