TY - GEN
T1 - Linear iterative turbo-equalization (LITE) for dual channels
AU - Singer, A.
AU - Nelson, J.
AU - Koetter, R.
N1 - Publisher Copyright:
© 1999 IEEE.
PY - 1999
Y1 - 1999
N2 - We examine a point-To-point communications scenario in which two or more separate, but known, channels are available for data transmission. While sending the same data across multiple channels provides channel diversity, we introduce additional temporal diversity by permuting the order of the data prior to transmission over one or more of the channels. As a receiver, we introduce a low complexity iterative equalization algorithm, inspired by iterative decoders for turbo-codes, which we call linear iterative turbo-equalization (LITE). The LITE algorithm contains one minimum mean square error linear equalizer for each channel and passes soft-information between the different equalizers in the form of a prior over the transmitted data. The linear equalizers differ from conventional equalizers by incorporating this prior in the minimization. Through simulations, we compare the empirical performance of the LITE algorithm to that of conventional linear and decision feedback equalizers, as well as maximum likelihood decoding for the set of channels. Our simulations demonstrate that the LITE algorithm can achieve equalization performance comparable to maximum likelihood decoding with computational complexity comparable to that of linear equalization.
AB - We examine a point-To-point communications scenario in which two or more separate, but known, channels are available for data transmission. While sending the same data across multiple channels provides channel diversity, we introduce additional temporal diversity by permuting the order of the data prior to transmission over one or more of the channels. As a receiver, we introduce a low complexity iterative equalization algorithm, inspired by iterative decoders for turbo-codes, which we call linear iterative turbo-equalization (LITE). The LITE algorithm contains one minimum mean square error linear equalizer for each channel and passes soft-information between the different equalizers in the form of a prior over the transmitted data. The linear equalizers differ from conventional equalizers by incorporating this prior in the minimization. Through simulations, we compare the empirical performance of the LITE algorithm to that of conventional linear and decision feedback equalizers, as well as maximum likelihood decoding for the set of channels. Our simulations demonstrate that the LITE algorithm can achieve equalization performance comparable to maximum likelihood decoding with computational complexity comparable to that of linear equalization.
UR - https://www.scopus.com/pages/publications/0033348142
U2 - 10.1109/ACSSC.1999.832031
DO - 10.1109/ACSSC.1999.832031
M3 - Conference contribution
AN - SCOPUS:0033348142
T3 - Conference Record of the 33rd Asilomar Conference on Signals, Systems, and Computers
SP - 1670
EP - 1674
BT - Conference Record of the 33rd Asilomar Conference on Signals, Systems, and Computers
A2 - Matthews, Michael B.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd Asilomar Conference on Signals, Systems, and Computers, ACSSC 1999
Y2 - 24 October 1999 through 27 October 1999
ER -