Waheed Uz Zaman Bajwa, “New Information Processing theory and Methods for Exploiting Sparsity Inwireless SystemS,” Ph.D. Thesis, University Of Wisconsin-Madison, 2007.

has been cited by the following article:

• TITLE: Estimation of Non-WSSUS Channel for OFDM Systems in High Speed Railway Environment Using Compressive Sensing

  AUTHORS: Chen Wang, Yong Fang, Zhi-Chao Sheng

  KEYWORDS: OFDM; Non-WSSUS Channel Estimation; Compressive Sensing (CS); Kalman Filter; LTE-R

  JOURNAL NAME: Communications and Network, Vol.5 No.3C, October 10, 2013

  ABSTRACT: Non Wide Sense Stationary Uncorrelated Scattering (Non-WSSUS) is one of characteristics for high-speed railway wireless channels. In this paper, estimation of Non-WSSUS Channel for OFDM Systems is considered by using Compressive Sensing (CS) method. Given sufficiently wide transmission bandwidth, wireless channels encountered here tend to exhibit a sparse multipath structure. Then a sparse Non-WSSUS channel estimation approach is proposed based on the delay-Doppler-spread function representation of the channel. This approach includes two steps. First, the delay-Doppler-spread function is estimated by the Compressive Sensing (CS) method utilizing the delay-Doppler basis. Then, the channel is tracked by a reduced order Kalman filter in the sparse delay-Doppler domain, and then estimated sequentially. Simulation results under LTE-R standard demonstrate that the proposed algorithm significantly improves the performance of channel estimation, comparing with the conventional Least Square (LS) and regular CS methods.