• Journal of Communications and Networks
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• v.16 no.1
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• pp.26-35
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• 2014

We consider multiple-input multiple-output decode-and-forward relay systems in Rayleigh fading channels under the partial channel state information (CSI) that the channel statistics of the source-relay (SR) link and the instantaneous CSI of the source-destination and relay-destination links are known at the destination. In this paper, we propose a new near maximum likelihood (near-ML) decoder with two-level pairwise error probability (near-ML-2PEP) which uses the average PEP instead of the exact PEP. Then, we theoretically prove that the near-ML and near-ML-2PEP decoders achieve the maximum diversity, which is confirmed by Monte Carlo simulations. Moreover, we show that the near-ML-2PEP decoder can also achieve the maximum diversity by substituting the average PEP with the values that represent the error performance of the SR link.

• 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.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.830-839
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• 2009

In this paper, we address a near maximum likelihood (ML) scheme for the decoding of multiple input multiple output systems. Based on the metric-first search method and by employing Schnorr-Euchner enumeration and branch length thresholds, the proposed scheme provides reduced computational complexity. The proposed scheme is shown by simulation to have lower computational complexity than other near ML decoders while maintaining the bit error rate close to the ML performance.

• ETRI Journal
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• v.41 no.2
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• pp.145-159
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• 2019

To reduce the number of radio frequency (RF) chains in multiple input multiple output (MIMO) systems, generalized spatial modulation (GSM) techniques have been proposed in the literature. In this paper, we propose a zero-forcing (ZF)-based detector, which performs an initial pruning of the search tree that will be considered as the initial condition in a sphere decoding (SD) algorithm. The proposed method significantly reduces the computational complexity of GSM systems while achieving a near maximum likelihood (ML) performance. We analyze the performance of the proposed method and provide an analytic performance difference between the proposed method and the ML detector. Simulation results show that the performance of the proposed method is very close to that of the ML detector, while achieving a significant computational complexity reduction in comparison with the conventional SD method, in terms of the number of visited nodes. We also present some simulations to assess the accuracy of our theoretical results.