TY - GEN
T1 - EM-based sparse channel estimation in OFDM systems with ℓq-norm regularization in the presence of phase noise and frequency offset
AU - Carvajal, Rodrigo
AU - Agüero, Juan C.
AU - Godoy, Boris I.
AU - Katselis, Dimitrios
N1 - Funding Information:
The work of R. Carvajal was supported by Chile's National Fund for Scientific and Technological Development (FONDECYT) through its Postdoctoral Fellowship Programme 2014 - Grant No 3140054. The work of J. C. Ag?ero was supported by FONDECYT through grant No 1150954. This work was partially supported by the Scientific Technological Centre of Valpara?so (CCTVal, Proyecto Basal FB0821), Chile.
Publisher Copyright:
© 2015 IEEE.
PY - 2016/3/9
Y1 - 2016/3/9
N2 - In this paper, we consider the problem of estimating sparse communication channels in orthogonal frequency division multiplexing systems with phase noise and carrier frequency offset. We consider the utilization of the ℓq-norm of the channel as a sparsity-promoting regularization term. The corresponding regularized likelihood cost function is expressed in a Bayesian fashion as a Maximum a Posteriori problem, from which the regularization term is expressed as an a priori distribution for the channel. Given the presence of hidden variables (i.e. the phase noise), the Expectation-Maximization algorithm is utilized. We show that the E-step in the proposed algorithm has a closed-form solution for the channel impulse response. In addition, this approach is an extension of previous work of the authors, which covers the popular Lasso.
AB - In this paper, we consider the problem of estimating sparse communication channels in orthogonal frequency division multiplexing systems with phase noise and carrier frequency offset. We consider the utilization of the ℓq-norm of the channel as a sparsity-promoting regularization term. The corresponding regularized likelihood cost function is expressed in a Bayesian fashion as a Maximum a Posteriori problem, from which the regularization term is expressed as an a priori distribution for the channel. Given the presence of hidden variables (i.e. the phase noise), the Expectation-Maximization algorithm is utilized. We show that the E-step in the proposed algorithm has a closed-form solution for the channel impulse response. In addition, this approach is an extension of previous work of the authors, which covers the popular Lasso.
UR - http://www.scopus.com/inward/record.url?scp=84964725491&partnerID=8YFLogxK
U2 - 10.1109/LATINCOM.2015.7430112
DO - 10.1109/LATINCOM.2015.7430112
M3 - Conference contribution
AN - SCOPUS:84964725491
T3 - 2015 7th IEEE Latin-American Conference on Communications, LATINCOM 2015
BT - 2015 7th IEEE Latin-American Conference on Communications, LATINCOM 2015
A2 - Fernandez Del Carpio, Gonzalo M.
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 November 2015 through 6 November 2015
ER -