IEICE TRANSACTIONS on Communications
Diversity Analysis of MIMO Decode-and-Forward Relay Network by Using Near-ML Decoder
Summary :
The probability of making mistakes on the decoded signals at the relay has been used for the maximum-likelihood (ML) decision at the receiver in the decode-and-forward (DF) relay network. It is well known that deriving the probability is relatively easy for the uncoded single-antenna transmission with M-pulse amplitude modulation (PAM). However, in the multiplexing multiple-input multiple-output (MIMO) transmission, the multi-dimensional decision region is getting too complicated to derive the probability. In this paper, a high-performance near-ML decoder is devised by applying a well-known pairwise error probability (PEP) of two paired-signals at the relay in the MIMO DF relay network. It also proves that the near-ML decoder can achieve the maximum diversity of MSMD+MR min (MS,MD), where MS, MR, and MD are the number of antennas at the source, relay, and destination, respectively. The simulation results show that 1) the near-ML decoder achieves the diversity we derived and 2) the bit error probability of the near-ML decoder is almost the same as that of the ML decoder.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E94-B No.10 pp.2828-2836
- Publication Date
- 2011/10/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E94.B.2828
- Type of Manuscript
- PAPER
- Category
- Wireless Communication Technologies
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Keyword
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Xianglan JIN, Dong-Sup JIN, Jong-Seon NO, Dong-Joon SHIN, "Diversity Analysis of MIMO Decode-and-Forward Relay Network by Using Near-ML Decoder" in IEICE TRANSACTIONS on Communications,
vol. E94-B, no. 10, pp. 2828-2836, October 2011, doi: 10.1587/transcom.E94.B.2828.
Abstract: The probability of making mistakes on the decoded signals at the relay has been used for the maximum-likelihood (ML) decision at the receiver in the decode-and-forward (DF) relay network. It is well known that deriving the probability is relatively easy for the uncoded single-antenna transmission with M-pulse amplitude modulation (PAM). However, in the multiplexing multiple-input multiple-output (MIMO) transmission, the multi-dimensional decision region is getting too complicated to derive the probability. In this paper, a high-performance near-ML decoder is devised by applying a well-known pairwise error probability (PEP) of two paired-signals at the relay in the MIMO DF relay network. It also proves that the near-ML decoder can achieve the maximum diversity of MSMD+MR min (MS,MD), where MS, MR, and MD are the number of antennas at the source, relay, and destination, respectively. The simulation results show that 1) the near-ML decoder achieves the diversity we derived and 2) the bit error probability of the near-ML decoder is almost the same as that of the ML decoder.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E94.B.2828/_p
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@ARTICLE{e94-b_10_2828,
author={Xianglan JIN, Dong-Sup JIN, Jong-Seon NO, Dong-Joon SHIN, },
journal={IEICE TRANSACTIONS on Communications},
title={Diversity Analysis of MIMO Decode-and-Forward Relay Network by Using Near-ML Decoder},
year={2011},
volume={E94-B},
number={10},
pages={2828-2836},
abstract={The probability of making mistakes on the decoded signals at the relay has been used for the maximum-likelihood (ML) decision at the receiver in the decode-and-forward (DF) relay network. It is well known that deriving the probability is relatively easy for the uncoded single-antenna transmission with M-pulse amplitude modulation (PAM). However, in the multiplexing multiple-input multiple-output (MIMO) transmission, the multi-dimensional decision region is getting too complicated to derive the probability. In this paper, a high-performance near-ML decoder is devised by applying a well-known pairwise error probability (PEP) of two paired-signals at the relay in the MIMO DF relay network. It also proves that the near-ML decoder can achieve the maximum diversity of MSMD+MR min (MS,MD), where MS, MR, and MD are the number of antennas at the source, relay, and destination, respectively. The simulation results show that 1) the near-ML decoder achieves the diversity we derived and 2) the bit error probability of the near-ML decoder is almost the same as that of the ML decoder.},
keywords={},
doi={10.1587/transcom.E94.B.2828},
ISSN={1745-1345},
month={October},}
Copy
TY - JOUR
TI - Diversity Analysis of MIMO Decode-and-Forward Relay Network by Using Near-ML Decoder
T2 - IEICE TRANSACTIONS on Communications
SP - 2828
EP - 2836
AU - Xianglan JIN
AU - Dong-Sup JIN
AU - Jong-Seon NO
AU - Dong-Joon SHIN
PY - 2011
DO - 10.1587/transcom.E94.B.2828
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E94-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2011
AB - The probability of making mistakes on the decoded signals at the relay has been used for the maximum-likelihood (ML) decision at the receiver in the decode-and-forward (DF) relay network. It is well known that deriving the probability is relatively easy for the uncoded single-antenna transmission with M-pulse amplitude modulation (PAM). However, in the multiplexing multiple-input multiple-output (MIMO) transmission, the multi-dimensional decision region is getting too complicated to derive the probability. In this paper, a high-performance near-ML decoder is devised by applying a well-known pairwise error probability (PEP) of two paired-signals at the relay in the MIMO DF relay network. It also proves that the near-ML decoder can achieve the maximum diversity of MSMD+MR min (MS,MD), where MS, MR, and MD are the number of antennas at the source, relay, and destination, respectively. The simulation results show that 1) the near-ML decoder achieves the diversity we derived and 2) the bit error probability of the near-ML decoder is almost the same as that of the ML decoder.
ER -
English
