• Journal of Communications and Networks
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• v.16 no.6
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• pp.620-626
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• 2014

In this paper, we propose a parallel collaborative sphere decoder with a scalable architecture promising quasi-maximum likelyhood performance with a relatively small amount of computational resources. This design offers a hardware-friendly algorithm using a modified node operation through fixing the variable complexity of the critical path caused by the sequential nature of the conventional sphere decoder (SD). It also reduces the computational complexity compared to the fixed-complexity sphere decoder (FSD) algorithm by tree pruning using collaboratively operated node operators. A Monte Carlo simulation shows that our proposed design can be implemented using only half the parallel operators compared to the approach using an ideal fully parallel scheme such as FSD, with only about a 7% increase of the normalized decoding time for MIMO dimensions of $16{\times}16$ with 16-QAM modulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.4
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• pp.180-187
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• 2014

In this paper, a extension of a fixed-complexity sphere decoder (FSD) to perform interference signal detection and cancelling is proposed for downlink multiuser multiple input-multiple output (MIMO) communication system. It is based on the application of channel matrix expansion on generalized sphere decoder (GSD), and modification of the channel matrix ordering scheme to a FSD algorithm for interference detection. A Monte Carlo simulation shows that the proposed algorithm improves the receiver performance by 3 dB as compared to maximum likelihood detection without interference cancelling at 10% packet error rate in configuration of 702 Mbit/s datarate for four users respectively on IEEE802.11ac.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.577-582
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• 2008

In this paper, we present a scheme to overcome the worst case complexity of the sphere decoder. If the number of visited nodes reaches the threshold, the detected symbol vector is determined between two candidate symbol vectors. One candidate symbol vector is obtained from the demodulated output of ZF receiver which is initial stage of the sphere decoder. The other candidate symbol vector consists of two sub-symbol vectors. The first sub-symbol vector consists of lately visited nodes running from the most upper layer. The second one contains corresponding demodulated outputs of ZF receiver. Between these two candidate symbol vectors, the one with smaller euclidean distance to the received symbol vector is chosen as detected symbol vector. In addition, we show the upper bound of symbol error rate performance for the sphere decoder using the proposed scheme. In the simulation, the proposed scheme shows the significant reduction of the worst case complexity while having negligible SER performance degradation.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.11-19
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• 2014

In this paper, a low complexity parallel sphere decoder algorithm is proposed for high-order MIMO system. It reduces the computational complexity compared to the fixed-complexity sphere decoder (FSD) algorithm by static tree-pruning and dynamic tree-pruning using scalable node operators, and offers near-maximum likelihood decoding performance. Moreover, it also offers hardware-friendly node operation algorithm through fixing the variable computational complexity caused by the sequential nature of the conventional SD algorithm. A Monte Carlo simulation shows our proposed algorithm decreases the average number of expanded nodes by 55% with only 6.3% increase of the normalized decoding time compared to a full parallelized FSD algorithm for high-order MIMO communication system with 16 QAM modulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.890-893
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• 2008

In this paper, we present a low complexity modified multi-level sphere decoder (SD) for multiple-input multiple-output (MIMO) systems employing quadrature amplitude modulation (QAM) signals. The proposed decoder, exploiting the multi-level structure of the QAM signal scheme, first decomposes the high-level constellation into low-level 4-QAM constellations, so-called sub-constellations. Then, it deploys SD in the sub-constellations in parallel. In addition, in the searching stage, it uses the optimal low-complexity sort method. Computer simulation results show that the proposed decoder can provide near optimal maximum-likelihood (ML) performance while it significantly reduces the computational load.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.567-571
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• 2008

In this paper, an overview on the ordering sphere decoder (SD) class for space-time codes (STC) will be presented. In SDs, the ordering techniques are considered as promising methods for reducing complexity by exploiting a sorted list of candidates, thus decreasing the number of tested points. First, we will present the current state of art of SD with their advantages and disadvantages. Then, the overview of simply geometrical approaches for ordering is presented to address the question to overcome the disadvantages. The computer simulation results shown that, thanks to the aid of ordering, the ordering SDs can achieve optimal bit-error-rate (BER) performance while requiring the very low complexity, which is comparable to that of linear sub-optimal decoders.

• ETRI Journal
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• v.36 no.4
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• pp.682-685
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• 2014

In this letter, we propose an efficient near-optimal detection scheme (that makes use of a generalized sphere decoder (GSD)) for blind multi-user multiple-input multiple-output (MU-MIMO) systems. In practical MU-MIMO systems, a receiver suffers from interference because the precoding matrix, the result of the precoding technique used, is quantized with limited feedback and is thus imperfect. The proposed scheme can achieve near-optimal performance with low complexity by using a GSD to detect several additional interference signals. In addition, the proposed scheme is suitable for use in blind systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.522-528
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• 2011

The iterative detection and decoding (IDD) has been shown to dramatically improve the bit error rate (BER) performance of the multiple-input multiple-output (MIMO) communication systems. However, these techniques require a high computational complexity since it is required to compute the soft decisions for each bit. In this paper, we show IDD comprised of sphere decoder with low-density parity check (LDPC) codes and present the tree search strategy, called a layer symbol search (LSS), to obtain soft decisions with a low computational complexity. In addition, an adaptive early termination is proposed to reduce the computational complexity during an iteration between an inner sphere decoder and an outer LDPC decoder. It is shown that the proposed approach can achieve the performance similar to an existing algorithm with 70% lower computational complexity compared to the conventional algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.888-894
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• 2007

The computational complexity of a sphere decoder (SD) is conventionally reduced by decoding order scheme which sorts candidate symbols in the ascending order of the Euclidean distance from the output of a zero-forcing (ZF) receiver. However, since the ZF output may not be a reliable sorting reference, we propose two types of sorting schemes to allow faster decoding. The first is to use the newly found lattice points in the previous search round instead of the ZF output (Type I). Since these lattice points are closer to the received signal than the ZF output, they can serve as a more reliable sorting reference for finding the maximum likelihood (ML) solution. The second sorting scheme is to sort candidate symbols in descending order according to the number of candidate symbols in the following layer, which are called child symbols (Type II). These two proposed sorting schemes can be combined with layer sorting for more complexity reduction. Through simulation, the Type I and Type II sorting schemes were found to provide 12% and 20% complexity reduction respectively over conventional sorting schemes. When they are combined with layer sorting, Type I and Type II provide an additional 10-15% complexity reduction while maintaining detection performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.494-507
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• 2011

In this paper, we propose two schemes to reduce the complexity of fixed-complexity sphere decoder (FSD) algorithm in the ordering and tree-search stages, respectively, while achieving quasi-ML performance. In the ordering stage, we propose a QR-decomposition-based FSD signal ordering based on the zero-forcing criterion (FSD-ZF-SQRD) that requires only a few number of additional complex flops compared to the unsorted QRD. Also, the proposed ordering algorithm is extended using the minimum mean square error (MMSE) criterion to achieve better performance. In the tree-search stage, we introduce a threshold-based complexity reduction approach for the FSD depending on the reliability of the signal with the largest noise amplification. Numerical results show that in 8 ${\times}$ 8 MIMO system, the proposed FSD-ZF-SQRD and FSD-MMSE-SQRD only require 19.5% and 26.3% of the computational efforts required by Hassibi's scheme, respectively. Moreover, a third threshold vector is outlined which can be used for high order modulation schemes. In 4 ${\times}$ 4 MIMO system using 16-QAM and 64-QAM, simulation results show that when the proposed threshold-based approach is employed, FSD requires only 62.86% and 53.67% of its full complexity, respectively.