• Journal of information and communication convergence engineering
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• v.4 no.2
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• pp.79-83
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• 2006

We present two techniques based on lookup tables to reduce complexity of the well-known Schnorr-Euchner (SE) sphere decoder (SD) without introducing performance degradation. By the aid of lookup tables, the computational loads caused by the SE enumeration and decision feedback are reduced at the cost of higher storage capacity. Simulation results are provided to verify performance and complexity of the proposed decoders.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3A
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• pp.231-237
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• 2010

Multi-input multi-output (MIMO) systems are used to improve the transmission rate in proportion to the number of antennas. However, their computational complexity is very high for the detection in the receiver. The sphere decoding (SD) is a detection algorithm with reduced complexity. In this paper, an improved Schnorr-Euchner SD (SE SD) is proposed based on the minimum mean square error (MMSE) and the Euclidean distance criteria without additional complexity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.120-124
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• 2006

We present two techniques based on lookup tables to reduce complexity of the well-known Schnorr-Euchner (SE) sphere decoder (SD) without introducing performance degradation. By the aid of lookup tables, the computational loads caused by the SE enumeration and decision feedback are reduced at the cost of higher storage capacity. Simulation results are provided to verify performance and complexity of the proposed decoders.

• 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.