A Low-Complexity ML Detector for Generalized Spatial Modulation Based on Priority 


Vol. 42,  No. 4, pp. 731-738, Apr.  2017


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  Abstract

In this paper, we proposed a modified ML detector for generalized spatial modulation which is a method among Multiple-input Multiple-output. This proposed method detects signal applying modified channel statement information based on priority. Complexity in conventional methods increases as increasing the number of active antennas. To solve this problem, we proposed a new ML method using static channel information decided by the number of transmit antennas and the number of receive antennas. This method detects active antennas one by one through priority. The proposed method has proved benefit on complexity compared with conventional method through simulations. When the number of transmit antennas is equal to 10, there is approximately 45% complexity reduction.

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  Cite this article

[IEEE Style]

M. H. Lee and S. Y. Shin, "A Low-Complexity ML Detector for Generalized Spatial Modulation Based on Priority," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 4, pp. 731-738, 2017. DOI: .

[ACM Style]

Man Hee Lee and Soo Young Shin. 2017. A Low-Complexity ML Detector for Generalized Spatial Modulation Based on Priority. The Journal of Korean Institute of Communications and Information Sciences, 42, 4, (2017), 731-738. DOI: .

[KICS Style]

Man Hee Lee and Soo Young Shin, "A Low-Complexity ML Detector for Generalized Spatial Modulation Based on Priority," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 4, pp. 731-738, 4. 2017.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880