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Estimation of Channel Parameters in a Multipath Environment via Optimizing Highly Oscillatory Error-Functions Using a Genetic Algorithm

机译:通过使用遗传算法优化高度振荡误差函数的多径环境中的信道参数估计

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Channel estimation is of crucial importance for tomorrow's wireless mobile communication systems. This paper focuses on the solution of channel parameters estimation problem in a scenario involving multiple paths in the presence of additive white Gaussian noise. We assumed that number of paths in the multipath environment is known and the transmitted signal consists of attenuated and delayed replicas of a known transient signal. In order to determine the maximum likelihood estimates one has to solve a complicated optimization problem. Genetic Algorithms (GA) are well known for their robustness in solving complex optimization problems. A GA is considered to extract channel parameters to minimize the derived error-function. The solution is based on the maximum-likelihood estimation of the channel parameters. Simulation results also demonstrate GA's robustness to channel parameters estimation errors.
机译:信道估计对于明天的无线移动通信系统至关重要。本文重点介绍了涉及添加性白色高斯噪声的多条路径的场景中信道参数估计问题的解决方案。我们假设已知多路径环境中的路径数,并且发送信号由已知瞬态信号的衰减和延迟副本组成。为了确定最大可能性估计,一个人必须解决复杂的优化问题。遗传算法(GA)在解决复杂优化问题时众所周知。遗传算法被认为提取通道参数以最小化派生误差函数。该解决方案基于信道参数的最大似然估计。仿真结果还展示了GA对信道参数估计错误的鲁棒性。

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