Diversity Analysis of MIMO Decode-and-Forward Relay Network by Using Near-ML Decoder
- Authors
- Jin, Xianglan; Jin, Dong-Sup; No, Jong-Seon; Shin, Dong-Joon
- Issue Date
- Oct-2011
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- decode-and-forward (DF); diversity; maximum-likelihood (ML); multiple-input multiple-output (MIMO); pairwise error probability (PEP); relay
- Citation
- IEICE TRANSACTIONS ON COMMUNICATIONS, v.E94B, no.10, pp.2828 - 2836
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEICE TRANSACTIONS ON COMMUNICATIONS
- Volume
- E94B
- Number
- 10
- Start Page
- 2828
- End Page
- 2836
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/167473
- DOI
- 10.1587/transcom.E94.B.2828
- ISSN
- 0916-8516
- 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 M-S M-D + M-R Min(M-S, M-D), where M-S, M-R, and M-D 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.
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