학술논문

Structured compressed sensing-based time-frequency joint channel estimation for MIMO-OFDM systems
Document Type
Conference
Source
2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA) Industrial Electronics and Applications (ICIEA), 2018 13th IEEE Conference on. :2006-2010 May, 2018
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Channel estimation
OFDM
MIMO communication
Estimation
Sensors
Time-frequency analysis
MIMO systems
channel estimation
TFT-OFDM
structured compression sensing (SCS)
Language
ISSN
2158-2297
Abstract
This paper proposes a time-frequency joint channel estimation method based on structured compression sensing (SCS) for multi-input and multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, which is different from traditional channel estimation scheme. In the proposed method, the received time-domain training sequences (TSs) without interference cancellation are exploited to obtain the coarse MIMO channel estimation of the path delays. By utilizing structured compression sensing method, furthermore a priori information-assisted adaptive structured subspace pursuit (PA-ASSP) algorithm which adopts a small amount of frequency domain orthogonal pilots is proposed to reconstruct the channel impulse response (CIR) of the MIMO channel so that the accurate channel gains is obtained. The simulation results show that the proposed scheme can more accurately estimate the channel with fewer pilots, and its performance is closer to the least squares (LS) algorithm.