Wavelet-based Subspace Method for Blind Estimation of Time-Varying Channels
A novel linear algorithm is proposed in this paper for estimating time-varying channels only relying on second order statistics. The proposed methods are applicable to channels where time-varying impulse response can be described as a linear combination of a finite number of wavelet basis functions. It is shown that the estimation of the wavelet expansion coefficients is equivalent to estimating the second-order parameters of an unobservable single input many output process, which are directly computed from the observation data. By exploiting this equivalence, blind subspace methods are applicable. Some illustrative simulations are presented.
Blind estimation Time-varying channel Subspace method Wavelet expansion
WANG Yongchuan BIAN Yongqing JIANG Tao
Department of Optical & Electronic Engineering, Ordnance Engineering College, Shijiazhuang, China, 0 Hebei University of Economic & Business, Shijiazhuang, China, 050061
国际会议
上海
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）