Adaptive control of surviving symbol replica candidates in QRM-MLD for OFDM MIMO multiplexing

Kawai, H.; Higuchi, Kenichi; Maeda, Noriko; Sawahashi, Mamoru

doi:10.1109/jsac.2005.864027

Cited by 100 publications

(47 citation statements)

References 17 publications

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“…In this work, for simplicity, we use , where the value of radius is predetermined as described in Section II. Two separate and independent candidate searches for two groups of antennas are represented by (10) and (12). The computational complexity of the presented detection approach is reduced compared to the QRD-M algorithm thanks to a lower complexity of these two partial candidate searches.…”

Section: Qrd-qld-based Parallel Candidate-search Algorithmmentioning

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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Section: Qrd-qld-based Parallel Candidate-search Algorithmmentioning

confidence: 99%

mentioning

confidence: 99%

Parallel Searching-Based Sphere Detector for MIMO Downlink OFDM Systems

Radosavljevic

Kim

Shen

et al. 2012

IEEE Trans. Signal Process.

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“…Hence, the detection throughput is nonfixed, which is not desirable for real-time hardware implementation. To resolve this problem, an MLD with QR decomposition and an M-algorithm (QRM-MLD) [12,13] was proposed. At each search layer in QRM-MLD, only the best M candidates are kept for the next level search and therefore, it has a fixed complexity and throughput that is suitable for the pipeline hardware implementation.…”

Section: Introductionmentioning

confidence: 99%

“…At each search layer in QRM-MLD, only the best M candidates are kept for the next level search and therefore, it has a fixed complexity and throughput that is suitable for the pipeline hardware implementation. However, since these algorithms, which are based on the tree search, rely on the computation of many path metrics by using QR decomposition, the complexity is still exponentially increasing with the number of transmit antennas [12].…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity and Low-Power MIMO Symbol Detector for Mobile Devices with Two TX/RX Antennas

Jang¹,

Lee²,

Jung

2015

JSTS:Journal of Semiconductor Technology and Science

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Abstract-In this paper, a low-complexity and lowpower soft output multiple input multiple output (MIMO) symbol detector is proposed for mobile devices with two transmit and two receive antennas. The proposed symbol detector can support both the spatial multiplexing mode and spatial diversity mode in single hardware and shows the optimal maximum likelihood (ML) performance. By applying a multistage pipeline structure and using a complex multiplier based on the polar-coordinate, the complexity of the proposed architecture is dramatically decreased. Also, by applying a clockgating scheme to the internal modules for MIMO modes, the power consumption is also reduced. The proposed symbol detector was designed using a hardware description language (HDL) and implemented using a 65nm CMOS standard cell library. With the proposed architecture, the proposed MIMO detector takes up an area of approximately 0.31mm 2 with 183K equivalent gates and achieves a 150Mbps throughput. Also, the power estimation results show that the proposed MIMO detector can reduce the power consumption by a maximum of 85% for the various test cases.

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“…These include an adaptive QRD-M [7], a partial decision feedback (PDF) QRD-M [8] and a very low complexity (VLC) QRD-M [9]. However, there are more or less limitations in these methods.…”

Section: Introductionmentioning

confidence: 99%

A Modified QRD-M Algorithm Based on Layer Branch Pruning for MIMO Systems

Xue

Hei

et al. 2010

2010 24th IEEE International Conference on Advanced Information Networking and Applications

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In this paper, a low complexity Modified QRD-M (MQRD-M) algorithm based on limited tree search is proposed for MIMO systems. The sphere radius and candidate set of each branch are considered to reduce the computational complexity. The sphere radius is efficiently acquired through the QRD detection based on pruning off unnecessary survival branches at each layer. Moreover, the candidate set of each branch is used to cut down the metric computation for it is much smaller than modulation set. Simulation results show that the proposed MQRD-M algorithm can achieve near-MLD performance and its average metric computation is lower than conventional QRD-M algorithms.

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Adaptive control of surviving symbol replica candidates in QRM-MLD for OFDM MIMO multiplexing

Cited by 100 publications

References 17 publications

Parallel Searching-Based Sphere Detector for MIMO Downlink OFDM Systems

Parallel Searching-Based Sphere Detector for MIMO Downlink OFDM Systems

Low-Complexity and Low-Power MIMO Symbol Detector for Mobile Devices with Two TX/RX Antennas

A Modified QRD-M Algorithm Based on Layer Branch Pruning for MIMO Systems

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