• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.10-18
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• 2013

Recently, a fixed complexity LR(fcLR) technique was proposed. Also QR-LRL signal detection method was proposed in which all constellation symbols are tried as the symbol corresponding to the least reliable layer (LRL), thereby achieving high error performance. In this paper, we combine these two efficient methods to propose a novel detection method. When the LRL is disregarded in the process of LR, the worst case complexity of LR is significantly reduced. Also, the proposed method is shown to be superior to the conventional fcLR-based detection method from the perspective of error performance. Simulations are performed to demonstrate the efficacy of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.634-641
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• 2009

The goal of OSIC-series detection methods is to approach the ML performance with feasible complexity. However, since they sometimes suffer from the empty vector problem, they can not achieve the soft-output ML performance or many candidate vectors are required to achieve the soft-output ML performance. In this paper, we propose the novel detection method, which can generate the reliable soft-outputs without suffering from empty vector problem. The proposed detector can approach the near soft-output ML performance as well as hard-output. Further, the complexity study shows that the proposed detection method has the lowest complexity compared to the other detectors having the near ML performance.