2012
DOI: 10.1049/iet-com.2012.0173
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Two-stage constellation partition algorithm for reduced-complexity multiple-input multiple-output–maximum-likelihood detection systems

Abstract: This study presents the analysis of a constellation partition (CP) algorithm for multiple-input multiple-outputmaximum-likelihood detection (MIMO -MLD) systems. The authors consider an N t by N r MIMO system, where MLD algorithm is employed at the receiver side for MIMO signal detection. The authors show that for the case of orthogonal space-time block codes and MIMO beamforming (MIMO-BF) systems, the proposed CP algorithm achieves the same errorrate performance as the optimum MLD algorithm while cutting back … Show more

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Cited by 4 publications
(3 citation statements)
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“…In contrast, classic MUD schemes, such as Minimum Mean Square Error (MMSE) and Order Successive Interference Cancellation (OSIC) have low performance but have the advantage of low complexity. As a result, some researchers have devoted their energy to developing suboptimum techniques and algorithms that can reach near-optimal performance with reduced computation complexity [7][8][9][10][11][12].…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, classic MUD schemes, such as Minimum Mean Square Error (MMSE) and Order Successive Interference Cancellation (OSIC) have low performance but have the advantage of low complexity. As a result, some researchers have devoted their energy to developing suboptimum techniques and algorithms that can reach near-optimal performance with reduced computation complexity [7][8][9][10][11][12].…”
Section: Introductionmentioning
confidence: 99%
“…Multiple input multiple output (MIMO) systems with rich scattering wireless channels can provide capacity enormously without increasing the bandwidth [1]. In order to decode symbols corrupted by inter-antenna interference, efficient signal detection methods for MIMO systems have been proposed in recent years [2]- [3].…”
Section: Introductionmentioning
confidence: 99%
“…Maximum Likelihood (ML) detection [8]- [9] algorithm detects all sub-stream symbols jointly by choosing the symbol vector with maximized likelihood function. From the viewpoint of symbol error rate, ML algorithm is optimal detection scheme.…”
Section: Introductionmentioning
confidence: 99%