TY - GEN
T1 - Iterative soft input decoding with assistance of lattice reduction for overloaded MIMO
AU - Denno, Satoshi
AU - Inoue, Tsubasa
AU - Fujiwara, Takuya
AU - Hou, Yafei
N1 - Funding Information:
This work has been supported by JSPS KAKENHI Grant Number JP18K04142 and NTT DoCoMo, Co.Ltd.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - This paper proposes an iterative low complexity soft input decoding with assistance of the lattice reduction for overloaded MIMO. The proposed soft input decoding applies two types of lattice reduction-aided linear filters to estimate log-likelihood ratio (LLR) in order to reduce the computational complexity. A lattice reduction-aided linear with whitening filter is introduced for the LLR estimation in the proposed decoding. The equivalent noise caused by the linear filter is mitigated with the decoder output streams and the LLR is re-estimated after the equivalent noise mitigation. Furthermore, LLR clipping is introduced in the proposed decoding to avoid the performance degradation due to the incorrect LLRs. The proposed decoding achieves about 2dB better BER performance than the soft decoding with the exhaustive search algorithm, so called the MLD, at the BER of 1.0E-4, even though the complexity of the proposed decoding is 1/10 as small as that of the soft decoding with the exhaustive search.
AB - This paper proposes an iterative low complexity soft input decoding with assistance of the lattice reduction for overloaded MIMO. The proposed soft input decoding applies two types of lattice reduction-aided linear filters to estimate log-likelihood ratio (LLR) in order to reduce the computational complexity. A lattice reduction-aided linear with whitening filter is introduced for the LLR estimation in the proposed decoding. The equivalent noise caused by the linear filter is mitigated with the decoder output streams and the LLR is re-estimated after the equivalent noise mitigation. Furthermore, LLR clipping is introduced in the proposed decoding to avoid the performance degradation due to the incorrect LLRs. The proposed decoding achieves about 2dB better BER performance than the soft decoding with the exhaustive search algorithm, so called the MLD, at the BER of 1.0E-4, even though the complexity of the proposed decoding is 1/10 as small as that of the soft decoding with the exhaustive search.
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U2 - 10.1109/VTCFall.2019.8891589
DO - 10.1109/VTCFall.2019.8891589
M3 - Conference contribution
AN - SCOPUS:85075246094
T3 - IEEE Vehicular Technology Conference
BT - 2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 90th IEEE Vehicular Technology Conference, VTC 2019 Fall
Y2 - 22 September 2019 through 25 September 2019
ER -