TY - GEN
T1 - Stochastic expectation maximization algorithm for long-memory fast-fading channels
AU - Wan, Hong
AU - Chen, Rong Rong
AU - Choi, Jun Won
AU - Singer, Andrew
AU - Preisig, James
AU - Farhang-Boroujeny, Behrouz
PY - 2010
Y1 - 2010
N2 - In this paper, we develop a novel statistical detection algorithm following similar principles to that of expectation maximization (EM) algorithm. Our goal is to develop an iterative algorithm for joint channel estimation and data detection in channels that have a long memory and are fast varying in time. At each iteration, starting with an estimate of the channel, we combine a Markov Chain Monte Carlo (MCMC) algorithm for data detection, and an adaptive algorithm for channel tracking, to develop a statistical search procedure that finds joint important samples of possible transmitted data and channel impulse responses. The result of this step, which may be thought as E-step of the proposed algorithm, is used in an M-step that refines the channel estimate, for the next iteration. Excellent behavior of the proposed algorithm is presented by examining it on real data from underwater acoustic communication channels.
AB - In this paper, we develop a novel statistical detection algorithm following similar principles to that of expectation maximization (EM) algorithm. Our goal is to develop an iterative algorithm for joint channel estimation and data detection in channels that have a long memory and are fast varying in time. At each iteration, starting with an estimate of the channel, we combine a Markov Chain Monte Carlo (MCMC) algorithm for data detection, and an adaptive algorithm for channel tracking, to develop a statistical search procedure that finds joint important samples of possible transmitted data and channel impulse responses. The result of this step, which may be thought as E-step of the proposed algorithm, is used in an M-step that refines the channel estimate, for the next iteration. Excellent behavior of the proposed algorithm is presented by examining it on real data from underwater acoustic communication channels.
KW - Markov chain Monte Carlo techniques
KW - Turbo equalization
KW - Underwater acoustic channels
UR - http://www.scopus.com/inward/record.url?scp=79551650965&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79551650965&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2010.5684346
DO - 10.1109/GLOCOM.2010.5684346
M3 - Conference contribution
AN - SCOPUS:79551650965
SN - 9781424456383
T3 - GLOBECOM - IEEE Global Telecommunications Conference
BT - 2010 IEEE Global Telecommunications Conference, GLOBECOM 2010
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 53rd IEEE Global Communications Conference, GLOBECOM 2010
Y2 - 6 December 2010 through 10 December 2010
ER -