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http://dx.doi.org/10.6109/jkiice.2017.21.3.516

Low-Complexity Robust ML Signal Detection for Generalized Spatial Modulation  

Kim, Jeong-Han (Department of Electrical and Information Engineering, Seoul National University of Science and Technology)
Yoon, Tae-Seon (Department of Electrical and Information Engineering, Seoul National University of Science and Technology)
Oh, Se-Hoon (Department of Electrical and Information Engineering, Seoul National University of Science and Technology)
Lee, Kyungchun (Department of Electrical and Information Engineering, Seoul National University of Science and Technology)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.21, no.3, 2017 , pp. 516-522 More about this Journal
Abstract
In this paper, we propose a maximum likelihood signal detection scheme for a generalized spatial modulation system that activates only a subset of transmit antennas among multiple antennas and transmits information through the indexes of active antennas as well as through the transmit symbols. The proposed maximum likelihood receiver extracts a set of candidate solutions based on their a posteriori probabilities to lower the computational load of the robust receiver under channel information errors. Then, the chosen candidate solutions are exploited to estimate the covariance matrix of effective noise. Simulation results show that the proposed maximum likelihood detection scheme achieves better error performance than a receiver that does not take into account the channel information errors. It is also seen that it reduces the computational complexity with the same bit error rate performance as the conventional robust maximum likelihood receiver.
Keywords
Spatial Modulation; Generalized Spatial Modulation; Channel Information Error; Maximum Likelihood Detection;
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Times Cited By KSCI : 2  (Citation Analysis)
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