Low-Complexity MIMO Data Detection using Seysen's Lattice Reduction Algorithm

Seethaler, D.; Matz, Gerald; Hlawatsch, Franz

doi:10.1109/icassp.2007.366470

Cited by 52 publications

(69 citation statements)

References 13 publications

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“…Remark: The proposed algorithm has a similar structure as that of the SA, and therefore, can be easily modified for complex bases as in [8]. Implementing the algorithm on the complex basis may have some complexity advantages as suggested by the study on complex LLL algorithm [5].…”

Section: Discussion On the Selection Of (P K)mentioning

confidence: 99%

“…Note that both the orthogonality measure and the Seysen's measure attain their minimum when the reduced basisB is orthogonal. For M ≤ 31, it has been observed that the SA is capable of finding bases with shorter basis vectors, when compared with the LLL [8,10].…”

Section: B Lr-aided Mimo Detectionmentioning

confidence: 99%

“…The performance of LR-aided MIMO detection based on LLL and SA has been studied and compared recently [8,14]. It has been shown that with the assistance of LR, full receive diversity of the MIMO fading channels can be achieved with low-complexity suboptimal detectors.…”

Section: Performance Of Lr-aided Linear Detectionmentioning

confidence: 99%

“…It has been shown that with the assistance of LR, full receive diversity of the MIMO fading channels can be achieved with low-complexity suboptimal detectors. For the case of linear detection, SA has been shown to consistently outperform the LLL algorithm in the sense of generating more orthogonal bases, thus providing lower error rate [8,14]. In [15], the author performed an analysis on the proximity factors and proposed to select the basis such that the minimum Euclidean distance from the received signal vector to the detector's decision boundary is maximized.…”

Section: Performance Of Lr-aided Linear Detectionmentioning

confidence: 99%

“…Recently, lattice-reduction (LR) has been introduced as a promising technique, which can improve the performance of many suboptimal MIMO detectors [3]- [8]. For LR-aided MIMO detection, the Lenstra-Lenstra-Lovász (LLL) algorithm [9] and the Seysen's algorithm (SA) [10] have been considered almost exclusively to date.…”

Section: Introductionmentioning

confidence: 99%

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A New Lattice Reduction Algorithm for LR-Aided MIMO Linear Detection

Chen

Sheen

2011

IEEE Trans. Wireless Commun.

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Abstract-Lattice reduction (LR) has recently emerged as a promising technique for improving the performance of suboptimal multiple-input-multiple-output (MIMO) detectors. For LRaided MIMO detection, the Lenstra-Lenstra-Lovász (LLL) and Seysen's algorithm (SA) have been considered almost exclusively to date. In this paper, we introduced a new LR algorithm for LR-aided linear detection (LD). In contrast to the LLL and SA, which are targeted to search for bases with relatively short basis vectors, the proposed algorithm has been designed to improve the minimum Euclidean distance of the LR-aided linear detector, thus exhibiting improved error rate at high SNR. The error-rate performance of the proposed algorithm as well as the required complexity has been demonstrated through extensive computer simulations.

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Section: Discussion On the Selection Of (P K)mentioning

confidence: 99%

Section: B Lr-aided Mimo Detectionmentioning

confidence: 99%

Section: Performance Of Lr-aided Linear Detectionmentioning

confidence: 99%

Section: Performance Of Lr-aided Linear Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A New Lattice Reduction Algorithm for LR-Aided MIMO Linear Detection

Chen

Sheen

2011

IEEE Trans. Wireless Commun.

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A Seysen's algorithm–based incremental lattice reduction

Schmeink

2019

Trans Emerging Tel Tech

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Lattice reduction (LR)–aided detections have attracted great attention in the symbol detection of multiple‐input–multiple‐output communication, especially for systems with larger scale antennas. Recently, the Lenstra‐Lenstra‐Lovász (LLL)–based incremental LR (ILR) algorithms have been proposed to employ an early termination to jointly conduct the LR and retrieve the symbol based on a partial successive interference cancellation (SIC) detection, which induces a significant performance improvement. In this paper, we propose to apply the Seysen's algorithm (SA) to the ILR. After providing the feasibility analysis, two novel SA involved algorithms are introduced and studied. In particular, a new sorted QR decomposition‐based SA algorithm is proposed and tested as it plays a key role in the SIC detection. Subsequently, a novel SA‐based ILR scheme is further developed and investigated. By simulations, we show that the proposed approach outperforms conventional LLL‐based ILR in various aspects, while only a marginal increment in the complexity, restricted to medium signal‐to‐noise‐ratio regions, is observed.

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Dual QR decomposition in K-best sphere detection for Internet of Things networks

Bokhari

Bhagyaveni

2017

Cluster Comput

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Low-Complexity MIMO Data Detection using Seysen's Lattice Reduction Algorithm

Cited by 52 publications

References 13 publications

A New Lattice Reduction Algorithm for LR-Aided MIMO Linear Detection

A New Lattice Reduction Algorithm for LR-Aided MIMO Linear Detection

A Seysen's algorithm–based incremental lattice reduction

Dual QR decomposition in K-best sphere detection for Internet of Things networks

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