2008
DOI: 10.3837/tiis.2008.04.003
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An Algorithm for Iterative Detection and Decoding MIMO-OFDM HARQ with Antenna Scheduling

Abstract: In this paper, a multiple-input-multiple-output (MIMO) hybrid-automatic repeat request (HARQ) algorithm with antenna scheduling is proposed. It retransmits the packet using scheduled transmit antennas according to the state of the communication link, instead of retransmitting the packet via the same antennas. As a result, a combination of conventional HARQ systems, viz. chase combining (CC) and incremental redundancy (IR) are used to achieve better performance and lower redundancy. The proposed MIMO-OFDM HARQ … Show more

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Cited by 5 publications
(3 citation statements)
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“…] T also denote the bit sequence mapped to X [p,q] . Given [ , ] H pq , Λ , and 2 s , the log-likelihood ratio (LLR) of x i , i Î {0,…, 2 Mp+ Mq -1} estimated using a mutiple-input mutiple-output (MIMO) maximum a posteriori (MAP) detector is written as [22], [23]…”
Section: Map Detection With Dual Phase Errors Compensationmentioning
confidence: 99%
See 1 more Smart Citation
“…] T also denote the bit sequence mapped to X [p,q] . Given [ , ] H pq , Λ , and 2 s , the log-likelihood ratio (LLR) of x i , i Î {0,…, 2 Mp+ Mq -1} estimated using a mutiple-input mutiple-output (MIMO) maximum a posteriori (MAP) detector is written as [22], [23]…”
Section: Map Detection With Dual Phase Errors Compensationmentioning
confidence: 99%
“…(1) 0   , the approximation of (1) , L ka for aÎ {p, q}, kÎ {0,1,…,N-1}\{a}, can be derived as a function of  as and similarly, the approximation of (2) , L ka for aÎ {p, q}, k Î {0,1,…,N-1}\{a}, can also be derived as a function of  as Therefore, by using the estimated dual phase errors (1) 0 L from (23), we can obtain estimates of ( 29) and ( 30 33) is repeated until all the data samples in an OFDM symbol are detected. This enables the following LDPC decoder to produce reliable a priori information in the first iteration.…”
Section: Successive Ici Cancellationmentioning
confidence: 99%
“…It has been shown that in wireless communications with multiple active users requesting services simultaneously, a technique called multiuser diversity (MD) can be exploited to increase the system achievable rate (AR) and reliability. In such a system, channel state information (CSI) is measured at all active users and then fed back to the base station (BS) whereby the packet scheduler at the medium‐access control (MAC) layer can allocate the system resources to the user having the best channel quality 10–12. More recently, the combination of cooperative diversity and MD has been considered in References 13 and 14.…”
Section: Introductionmentioning
confidence: 99%