Mapping for Iterative MMSE-SIC with Belief Propagation

Satoshi GOUNAI  Tomoaki OHTSUKI  Toshinobu KANEKO  

Publication
IEICE TRANSACTIONS on Communications   Vol.E91-B   No.7   pp.2187-2197
Publication Date: 2008/07/01
Online ISSN: 1745-1345
DOI: 10.1093/ietcom/e91-b.7.2187
Print ISSN: 0916-8516
Type of Manuscript: PAPER
Category: Fundamental Theories for Communications
Keyword: 
MIMO,  MMSE-SIC,  Belief Propagation,  Mapping,  

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Summary: 
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.