首页> 外文期刊>IEICE Transactions on Communications >Evolutional Algorithm Based Learning of Time Varying Multipath Fading Channels for Software Defined Radio
【24h】

Evolutional Algorithm Based Learning of Time Varying Multipath Fading Channels for Software Defined Radio

机译:基于进化算法的软件无线电无线电时变多径衰落信道学习

获取原文
获取原文并翻译 | 示例
           

摘要

Software defined radio, which uses reconfigurable signal processing devices, requires the determination of multiple unknown parameters to realize the potential capabilities of adaptive communication. Evolutional algorithms are optimal multi dimensional search techniques, and are well known to be effective for parameter determination. This letter proposes an evolutional algorithm for learning the mobile time-varying channel parameters without any specific assumption of scattering distribution. The proposed method is very simple to realize, but can provide precise channel estimation results. Simulations of an OFDM system show that for an example of OFDM communication under the time-varying fading channel, the proposed learning method can achieve the better BER performance.
机译:使用可重新配置的信号处理设备的软件定义无线电,需要确定多个未知参数才能实现自适应通信的潜在功能。进化算法是最佳的多维搜索技术,并且众所周知对于参数确定有效。这封信提出了一种进化算法,用于学习移动时变信道参数,而无需任何特定的散射分布假设。所提出的方法很容易实现,但是可以提供精确的信道估计结果。 OFDM系统的仿真表明,以时变衰落信道下的OFDM通信为例,该学习方法可以获得较好的BER性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号