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

机译:使用遗传算法和模拟退火的MC-CDMA系统的联合通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:在多载波码分割多址(MC-CDMA)系统中,多个访问干扰(MAI)是显着降低系统性能的关键因素。在该研究中,基因算法(GA)用于联合信道估计和多用户检测。为了提高Ga的探索和开发强度,通过将模拟的退火(SA)结合到突变操作来开发一种称为SAM-Ga的GA基方法。此外,提出了基于阈值的突变来细化SAM-GA方案。为简单起见,所得方案称为修改的SAM-GA。实验结果表明,所提出的修改的SAM-GA方案在MC-CDMA系统中为联合CIR估计和多用户检测的均方误差(MSE),误码率(BER)和收敛速度实现了最佳性能与其他方案相比。

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