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Adaptive K-best Sphere Decoding Algorithm Using the Characteristics of Path Metric  

Kim, Bong-Seok (영남대학교 정보통신공학과 광대역무선통신 연구실)
Choi, Kwon-Hue (영남대학교 정보통신공학과 광대역무선통신 연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.34, no.11A, 2009 , pp. 862-869 More about this Journal
Abstract
We propose a new adaptive K-best Sphere Decoding (SD) algorithm for Multiple Input Multiple Output (MIMO) systems where the number of survivor paths, K is changed based on the characteristics of path metrics which contain the instantaneous channel condition. In order to overcome a major drawback of Maximum Likelihood Detection (MLD) which exponentially increases the computational complexity with the number of transmit antennas, the conventional adaptive K-best SD algorithms which achieve near to MLD performance have been proposed. However, they still have redundant computation complexity since they only employ the channel fading gain as a channel condition indicator without instantaneous Signal to Noise Ratio (SNR) information. hi order to complement this drawback, the proposed algorithm use the characteristics of path metrics as a simple channel indicator. It is found that the ratio of the minimum path metric to the other path metrics reflects SNR information as well as channel fading gain. By adaptively changing K based on this ratio, the proposed algorithm more effectively reduce the computation complexity compared to the conventional K-best algorithms which achieve same performance.
Keywords
MIMO; Low Complexity; Tree-search; K-best;
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Times Cited By KSCI : 3  (Citation Analysis)
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