An Efficient Fixed Complexity QRD-M Algorithm for MIMO-OFDM using Per-Survivor Slicing

Detert, T.

doi:10.1109/iswcs.2007.4392405

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…The upper triangular matrix R is a key factor to realize the tree structure, where retaining paths are dependent on the diagonal components of R. Thus, an ill-conditioned channel matrix with a high condition number may result in significant degradation in MIMO systems [7]. Minimum mean-squared error (MMSE) based QRD-M (MQRD-M ) algorithms can effectively deal with this problem [8]. As a result, the MQRD-M algorithms provide improved performance gain compared to the conventional QRD-M algorithm.…”

Section: Introductionmentioning

confidence: 99%

Enhanced QRD-M algorithm for soft-output MIMO detection

Kim

2012

2012 IEEE Global Communications Conference (GLOBECOM)

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QR-decomposition with M algorithm is a promising technique for multi-input multi-output (MIMO) systems. When the number of candidates is insufficient, its performance is, however, degraded due to an inaccurate log likelihood ratio (LLR). To address this problem, an enhanced soft LLR calculation scheme is proposed for soft-output MIMO detection. Based on QR-decomposition, the proposed algorithm can efficiently obtain a soft information of minimum mean-squared error (MMSE) equalization. With this information, an optimal weighted combining method is derived in an MSE sense. In addition, we compute a more reliable clipping value from the soft information of MMSE equalization. Simulation results show that the proposed algorithm provides a considerable performance gain over conventional algorithms and its performance is close to optimal performance with insufficient candidates. Index Terms-Maximum-likelihood detection (MLD), Multiinput multi-output (MIMO), QR-decomposition, Log likelihood ratio (LLR) calculation

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Section: Introductionmentioning

confidence: 99%

Enhanced QRD-M algorithm for soft-output MIMO detection

Kim

2012

2012 IEEE Global Communications Conference (GLOBECOM)

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“…4 calculates a center of the hyper-sphere, as well as the common factors defined in (10) and (12) to test all symbol-candidates for each transmit antenna. The center of hypersphere can be defined as (13) Since is fully known, certain factors that are not dependent on the symbol-candidates being tested can be precomputed according to (14) The factors obtained in (14) can be saved in the registers and utilized in the appropriate search level . It can be observed that computing all products in (14) for each search level is not required.…”

Section: A Preprocessing Unitmentioning

confidence: 99%

“…The QRD-M detector has been well studied as a possible solution for downlink OFDM receivers employed in several emerging wireless standards, such as the 3GPP-LTE, IMT-Advanced, WLAN, WiMAX, etc. Using only a significantly reduced computational requirement, the QRD-M can approach near to the maximum likelihood detector (MLD) performance [5], [8]- [13]. However, since the original QRD-M detector still requires high computational complexity in calculating accumulated branch metrics, two categorized approaches have been proposed to reduce this problem.…”

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confidence: 99%

“…However, since the original QRD-M detector still requires high computational complexity in calculating accumulated branch metrics, two categorized approaches have been proposed to reduce this problem. In [5], [8]- [11], the required computations can be reduced by controlling a number of survivor paths, whereas a number of branch metrics being used in one survivor path at each detection stage is selected effectively using reliable symbol information [12], [13]. However, in these works, error-rate performance of the original QRD-M detector has been sacrificed for reduction in computational complexity.…”

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confidence: 99%

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Parallel Searching-Based Sphere Detector for MIMO Downlink OFDM Systems

Radosavljevic

Kim

Shen

et al. 2012

IEEE Trans. Signal Process.

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Abstract-In this paper, implementation of a detector with parallel partial candidate-search algorithm is described. Two fully independent partial candidate search processes are simultaneously employed for two groups of transmit antennas based on QR decomposition (QRD) and QL decomposition (QLD) of a multiple-input multiple-output (MIMO) channel matrix. By using separate simultaneous candidate searching processes, the proposed implementation of QRD-QLD searching-based sphere detector provides a smaller latency and a lower computational complexity than the original QRD-M detector for similar error-rate performance in wireless communications systems employing four transmit and four receive antennas with 16-QAM or 64-QAM constellation size. It is shown that in coded MIMO orthogonal frequency division multiplexing (MIMO OFDM) systems, the detection latency and computational complexity of a receiver can be substantially reduced by using the proposed QRD-QLD detector implementation. The QRD-QLD-based sphere detector is also implemented using Field Programmable Gate Array (FPGA) and application specific integrated circuit (ASIC), and its hardware design complexity is compared with that of other sphere detectors reported in the literature.Index Terms-ASIC, bounded soft sphere detector, Field Programmable Gate Array (FPGA), implementation complexity, latency analysis, QL decomposition (QLD), QR decomposition (QRD), QRD-M, QRD-QLD-based parallel candidate search.

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“…1 The QR Decompositon with an M-algorithm (QRD-M) can guarantee a fixed throughput while maintain a performance close to MLD [3] . So it is especially attractive to the high-throughput MIMO-OFDM systems and extensively studied recently [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A simplified QRD-M signal detection algorithm for MIMO-OFDM systems

Jian

Yao

Yin

2010

J. Electron.(China)

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QR Decompositon with an M-algorithm (QRD-M) has good performance with low complexity, which is considered as a promising technique in Multiple-Input Multiple-Output (MIMO) detections. This paper presented a simplified QRD-M algorithm for MIMO Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems. In the proposed scheme, each surviving path is expanded only to partial branches in order to carry out a limited tree search. The nodes are expanded on demand and sorted in a distributed manner, based on the novel expansion scheme which can pre-determine the children's ascending order by their local distances. Consequently, the proposed scheme can significantly decrease the complexity compared with conventional QRD-M algorithm. Hence, it is especially attractive to VLSI implementation of the high-throughput MIMO-OFDM systems. Simulation results prove that the proposed scheme can achieve a performance very close to the conventional QRD-M algorithm.

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An Efficient Fixed Complexity QRD-M Algorithm for MIMO-OFDM using Per-Survivor Slicing

Cited by 5 publications

References 11 publications

Enhanced QRD-M algorithm for soft-output MIMO detection

Enhanced QRD-M algorithm for soft-output MIMO detection

Parallel Searching-Based Sphere Detector for MIMO Downlink OFDM Systems

A simplified QRD-M signal detection algorithm for MIMO-OFDM systems

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