Multiple-Input Multiple-Output (MIMO) wireless systems offer both high data rates and high capacity. Since different signals are transmitted by different antennas simultaneously, interference occurs between the transmitted signals. Each receive antenna receives all the signals transmitted by each transmit antenna simultaneously. The receiver has to detect each signal from the multiplexed signal. A Minimum Mean Square Error (MMSE) algorithm is used for spatial filtering. MMSE filtering can realize low complexity signal detection, but the signal output by MMSE filtering suffers from interference by the other signals. MMSE-SIC combines MMSE filtering and Soft Interference Cancellation (SIC) with soft replicas and can achieve good Bit Error Rate (BER) performance. If an irregular LDPC code or a turbo code is used, the reliability and BER of the information bits output by the decoder are likely to be higher and better than the parity bits. In MMSE-SIC, bits with poor reliability lower the accuracy of soft replica estimation. When the soft replica is inaccurate, the gain obtained by SIC is small. M-ary Phase Shift Keying (PSK) and M-ary Quadrature Amplitude Modulation (QAM) also achieve high data rates. Larger constellations such as 8 PSK and 16 QAM transfer more bits per symbol, and the number of bits per symbol impacts the accuracy of SIC. Unfortunately, increasing the number of bits per symbol is likely to lower the accuracy of soft replica estimation. In this paper, we evaluate three mapping schemes for MMSE-SIC with an LDPC code and a turbo code with the goal of effectively increasing the SIC gain. The first scheme is information reliable mapping. In this scheme, information bits are assigned to strongly protected bits. In the second scheme, parity reliable mapping, parity bits are assigned to strongly protected bits. The last one is random mapping. Computer simulations show that in MMSE-SIC with an irregular LDPC code and a turbo code, information reliable mapping offers the highest SIC gain. We also show that in MMSE-SIC with the regular LDPC code, the gains offered by the mapping schemes are very small.
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Satoshi GOUNAI, Tomoaki OHTSUKI, Toshinobu KANEKO, "Mapping for Iterative MMSE-SIC with Belief Propagation" in IEICE TRANSACTIONS on Communications,
vol. E91-B, no. 7, pp. 2187-2197, July 2008, doi: 10.1093/ietcom/e91-b.7.2187.
Abstract: Multiple-Input Multiple-Output (MIMO) wireless systems offer both high data rates and high capacity. Since different signals are transmitted by different antennas simultaneously, interference occurs between the transmitted signals. Each receive antenna receives all the signals transmitted by each transmit antenna simultaneously. The receiver has to detect each signal from the multiplexed signal. A Minimum Mean Square Error (MMSE) algorithm is used for spatial filtering. MMSE filtering can realize low complexity signal detection, but the signal output by MMSE filtering suffers from interference by the other signals. MMSE-SIC combines MMSE filtering and Soft Interference Cancellation (SIC) with soft replicas and can achieve good Bit Error Rate (BER) performance. If an irregular LDPC code or a turbo code is used, the reliability and BER of the information bits output by the decoder are likely to be higher and better than the parity bits. In MMSE-SIC, bits with poor reliability lower the accuracy of soft replica estimation. When the soft replica is inaccurate, the gain obtained by SIC is small. M-ary Phase Shift Keying (PSK) and M-ary Quadrature Amplitude Modulation (QAM) also achieve high data rates. Larger constellations such as 8 PSK and 16 QAM transfer more bits per symbol, and the number of bits per symbol impacts the accuracy of SIC. Unfortunately, increasing the number of bits per symbol is likely to lower the accuracy of soft replica estimation. In this paper, we evaluate three mapping schemes for MMSE-SIC with an LDPC code and a turbo code with the goal of effectively increasing the SIC gain. The first scheme is information reliable mapping. In this scheme, information bits are assigned to strongly protected bits. In the second scheme, parity reliable mapping, parity bits are assigned to strongly protected bits. The last one is random mapping. Computer simulations show that in MMSE-SIC with an irregular LDPC code and a turbo code, information reliable mapping offers the highest SIC gain. We also show that in MMSE-SIC with the regular LDPC code, the gains offered by the mapping schemes are very small.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e91-b.7.2187/_p
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@ARTICLE{e91-b_7_2187,
author={Satoshi GOUNAI, Tomoaki OHTSUKI, Toshinobu KANEKO, },
journal={IEICE TRANSACTIONS on Communications},
title={Mapping for Iterative MMSE-SIC with Belief Propagation},
year={2008},
volume={E91-B},
number={7},
pages={2187-2197},
abstract={Multiple-Input Multiple-Output (MIMO) wireless systems offer both high data rates and high capacity. Since different signals are transmitted by different antennas simultaneously, interference occurs between the transmitted signals. Each receive antenna receives all the signals transmitted by each transmit antenna simultaneously. The receiver has to detect each signal from the multiplexed signal. A Minimum Mean Square Error (MMSE) algorithm is used for spatial filtering. MMSE filtering can realize low complexity signal detection, but the signal output by MMSE filtering suffers from interference by the other signals. MMSE-SIC combines MMSE filtering and Soft Interference Cancellation (SIC) with soft replicas and can achieve good Bit Error Rate (BER) performance. If an irregular LDPC code or a turbo code is used, the reliability and BER of the information bits output by the decoder are likely to be higher and better than the parity bits. In MMSE-SIC, bits with poor reliability lower the accuracy of soft replica estimation. When the soft replica is inaccurate, the gain obtained by SIC is small. M-ary Phase Shift Keying (PSK) and M-ary Quadrature Amplitude Modulation (QAM) also achieve high data rates. Larger constellations such as 8 PSK and 16 QAM transfer more bits per symbol, and the number of bits per symbol impacts the accuracy of SIC. Unfortunately, increasing the number of bits per symbol is likely to lower the accuracy of soft replica estimation. In this paper, we evaluate three mapping schemes for MMSE-SIC with an LDPC code and a turbo code with the goal of effectively increasing the SIC gain. The first scheme is information reliable mapping. In this scheme, information bits are assigned to strongly protected bits. In the second scheme, parity reliable mapping, parity bits are assigned to strongly protected bits. The last one is random mapping. Computer simulations show that in MMSE-SIC with an irregular LDPC code and a turbo code, information reliable mapping offers the highest SIC gain. We also show that in MMSE-SIC with the regular LDPC code, the gains offered by the mapping schemes are very small.},
keywords={},
doi={10.1093/ietcom/e91-b.7.2187},
ISSN={1745-1345},
month={July},}
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TY - JOUR
TI - Mapping for Iterative MMSE-SIC with Belief Propagation
T2 - IEICE TRANSACTIONS on Communications
SP - 2187
EP - 2197
AU - Satoshi GOUNAI
AU - Tomoaki OHTSUKI
AU - Toshinobu KANEKO
PY - 2008
DO - 10.1093/ietcom/e91-b.7.2187
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E91-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2008
AB - Multiple-Input Multiple-Output (MIMO) wireless systems offer both high data rates and high capacity. Since different signals are transmitted by different antennas simultaneously, interference occurs between the transmitted signals. Each receive antenna receives all the signals transmitted by each transmit antenna simultaneously. The receiver has to detect each signal from the multiplexed signal. A Minimum Mean Square Error (MMSE) algorithm is used for spatial filtering. MMSE filtering can realize low complexity signal detection, but the signal output by MMSE filtering suffers from interference by the other signals. MMSE-SIC combines MMSE filtering and Soft Interference Cancellation (SIC) with soft replicas and can achieve good Bit Error Rate (BER) performance. If an irregular LDPC code or a turbo code is used, the reliability and BER of the information bits output by the decoder are likely to be higher and better than the parity bits. In MMSE-SIC, bits with poor reliability lower the accuracy of soft replica estimation. When the soft replica is inaccurate, the gain obtained by SIC is small. M-ary Phase Shift Keying (PSK) and M-ary Quadrature Amplitude Modulation (QAM) also achieve high data rates. Larger constellations such as 8 PSK and 16 QAM transfer more bits per symbol, and the number of bits per symbol impacts the accuracy of SIC. Unfortunately, increasing the number of bits per symbol is likely to lower the accuracy of soft replica estimation. In this paper, we evaluate three mapping schemes for MMSE-SIC with an LDPC code and a turbo code with the goal of effectively increasing the SIC gain. The first scheme is information reliable mapping. In this scheme, information bits are assigned to strongly protected bits. In the second scheme, parity reliable mapping, parity bits are assigned to strongly protected bits. The last one is random mapping. Computer simulations show that in MMSE-SIC with an irregular LDPC code and a turbo code, information reliable mapping offers the highest SIC gain. We also show that in MMSE-SIC with the regular LDPC code, the gains offered by the mapping schemes are very small.
ER -