...
首页> 外文期刊>IEEE Transactions on Signal Processing >Sufficient conditions for the local convergence of constant modulus algorithms
【24h】

Sufficient conditions for the local convergence of constant modulus algorithms

机译:恒模算法局部收敛的充分条件

获取原文
获取原文并翻译 | 示例

摘要

The constant modulus (CM) criterion has become popular in the design of blind linear estimators of sub-Gaussian i.i.d. processes transmitted through unknown linear channels in the presence of unknown additive interference. The existence of multiple CM minima, however, makes it difficult for CM-minimizing schemes to generate estimates of the desired source (as opposed to an interferer) in multiuser environments. In this paper, we present three separate sufficient conditions under which gradient descent (GD) minimization of CM cost will locally converge to an estimator of the desired source at a particular delay. The sufficient conditions are expressed in terms of statistical properties of the initial estimates, specifically, CM cost, kurtosis, and signal-to-interference-plus-noise ratio (SINR). Implications on CM-GD initialization methods are also discussed.
机译:恒定模量(CM)准则已在次高斯i.i.d的盲线性估计器的设计中流行。存在未知加性干扰时通过未知线性通道传输的过程。但是,多个CM最小值的存在使CM最小化方案难以在多用户环境中生成所需源(与干扰源相对)的估计。在本文中,我们提出了三个独立的充分条件,在这些条件下,CM成本的梯度下降(GD)最小化将在特定延迟下局部收敛至所需源的估计量。足够的条件用初始估计的统计属性表示,具体来说就是CM成本,峰度和信号干扰加噪声比(SINR)。还讨论了对CM-GD初始化方法的影响。

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