Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

• Published in: IEEE transactions on signal processing Vol. 63; no. 20; pp. 5369 - 5382
• Main Authors: Prasad, Ranjitha, Murthy, Chandra R., Rao, Bhaskar D.
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.10.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Channel estimation; cluster sparsity; joint channel estimation and data detection; joint sparsity; Joints; Mean square errors; Monte Carlo simulation; multiple measurement vectors; OFDM; Receiving antennas; Signal processing algorithms; Sparse Bayesian learning; Transmitting antennas; Wireless communication

The impulse response of wireless channels between the Nt transmit and Nr receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., the NtNr channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths...