TY - JOUR

T1 - Nondata-aided joint channel estimation and equalization for OFDM systems in very rapidly varying mobile channels

AU - Şenol, Habib

AU - Panayirci, Erdal

AU - Poor, H. Vincent

N1 - Funding Information:
Manuscript received July 21, 2011; revised January 09, 2012 and March 24, 2012; accepted April 04, 2012. Date of publication April 20, 2012; date of current version July 10, 2012. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Sofiene Affes. This work was conducted within the NEWCOM++ Network of Excellence in Wireless Communications and WIMAGIC Strep projects funded through the EC 7th Framework Programs, and by the U.S. Air Force Office of Scientific Research under MURI Grant FA9550-09-1-0643.

PY - 2012

Y1 - 2012

N2 - This paper is concerned with the challenging and timely problem of joint channel estimation and equalization for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. The resulting algorithm is based on the space alternating generalized expectation maximization-maximum a posteriori probability (SAGE-MAP) technique which is particularly well suited to multicarrier signal formats. The algorithm is implemented in the time-domain which enables one to use the Gaussian approximation of the transmitted OFDM samples. Consequently, the averaging process of the nonpilot data symbols becomes analytically possible resulting in a feasible and computationally efficient channel estimation algorithm leading to a receiver structure that yields also an equalized output from which the data symbols are detected with excellent symbol error rate (SER) performance. Based on this Gaussian approximation the exact Bayesian Cramér Rao lower bound (CRLB) as well as the convergence rate of the algorithm are derived analytically. To reduce the computational complexity of the algorithm, discrete Legendre orthogonal basis functions are employed to represent the rapidly time-varying fading channel. It is shown that, depending on the normalized Doppler frequency, only a small number of expansion coefficients is sufficient to approximate the channel very well and there is no need to know the correlation function of the input signal. The computational complexity of the algorithm is shown to be ∼O(NL) per detected data symbol and per SAGE-MAP algorithm cycle where N is the number of OFDM subcarriers and L is the number of multipath components.

AB - This paper is concerned with the challenging and timely problem of joint channel estimation and equalization for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. The resulting algorithm is based on the space alternating generalized expectation maximization-maximum a posteriori probability (SAGE-MAP) technique which is particularly well suited to multicarrier signal formats. The algorithm is implemented in the time-domain which enables one to use the Gaussian approximation of the transmitted OFDM samples. Consequently, the averaging process of the nonpilot data symbols becomes analytically possible resulting in a feasible and computationally efficient channel estimation algorithm leading to a receiver structure that yields also an equalized output from which the data symbols are detected with excellent symbol error rate (SER) performance. Based on this Gaussian approximation the exact Bayesian Cramér Rao lower bound (CRLB) as well as the convergence rate of the algorithm are derived analytically. To reduce the computational complexity of the algorithm, discrete Legendre orthogonal basis functions are employed to represent the rapidly time-varying fading channel. It is shown that, depending on the normalized Doppler frequency, only a small number of expansion coefficients is sufficient to approximate the channel very well and there is no need to know the correlation function of the input signal. The computational complexity of the algorithm is shown to be ∼O(NL) per detected data symbol and per SAGE-MAP algorithm cycle where N is the number of OFDM subcarriers and L is the number of multipath components.

KW - Basis expansion model (BEM)

KW - SAGE-MAP algorithm

KW - joint channel estimation and equalization

KW - orthogonal frequency-division multiplexing (OFDM)

KW - rapidly varying wireless channels

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U2 - 10.1109/TSP.2012.2195657

DO - 10.1109/TSP.2012.2195657

M3 - Article

AN - SCOPUS:84863953708

VL - 60

SP - 4236

EP - 4253

JO - IEEE Transactions on Acoustics, Speech, and Signal Processing

JF - IEEE Transactions on Acoustics, Speech, and Signal Processing

SN - 1053-587X

IS - 8

M1 - 6188536

ER -