Abstract
Channel estimation is still a challenge for space time block coding (STBC) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems in time-varying environments. To estimate the channel state information (CSI) precisely without increasing complexity in any significant way, this paper utilizes the sparsity and the inherent temporal correlation of the time-varying wireless channel, and proposes a novel channel estimation method applied to STBC MIMO-OFDM systems. The proposed method consists of two schemes: adaptive multi-frame averaging (AMA) and improved mean square error (MSE) optimal threshold (IMOT). First, the temporal correlation of the time-varying channel is modeled by a linear Gauss-Markov (LGM) model, and the AMA scheme is incorporated to refine the initial estimated channel impulse response (CIR) through noise reduction. Based on the LGM model, the optimal average frame number is adaptively determined by minimizing the MSE of the denoised CIR. Then, the sparsity of the wireless channel is utilized to model the CIR as a sparse vector, and the IMOT scheme is performed to further remove the noise effect by discarding most of the noise-only CIR taps. Specifically, the IMOT scheme is achieved by recovering the CIR support across the optimal “tap-to-tap” threshold derived by minimizing the MSE of each CIR tap. Moreover, the prior confidence level of the tap to be active is calculated through multi-frame statistics to further improve the performance of the IMOT scheme. Simulation results verify that the proposed AMA-IMOT channel estimation method can achieve better performance than comparison methods.
Highlights
Based on the linear Gauss-Markov (LGM) model, the optimal average frame number is adaptively determined by minimizing the mean square error (MSE) of the denoised channel impulse response (CIR)
By utilizing the LGM model, the optimal average frame number is adaptively determined by minimizing the MSE of the denoised CIR
The IMOT scheme is achieved by recovering the CIR support across the optimal ‘‘tap-to-tap’’ threshold derived by minimizing the MSE of each CIR tap
Summary
Xie et al [40] propose a more rigorous universal threshold with a two-step iterative noise variance estimation method, which can greatly improve the estimation accuracy of the noise variance In this way [38]–[40], a dynamic number of MSTs is selected per OFDM symbol, and the noise effect can be effectively suppressed without any prior KCS during different SNR scenarios. By combining the multi-frame averaging method and the TBS method, this paper proposes an AWA and IMOT based channel estimation method in STBC MIMO-OFDM systems. SYSTEM MODEL A 2 × 2 STBC MIMO-OFDM system with N subcarriers and utilizing the proposed channel estimation method, is presented, where a space-time orthogonal pilot pattern [18] is used to avoid interference from other transmit antennas. The accuracy of channel estimation directly affects the recovery quality of the final received signals
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
