• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.43-50
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• 2007

In the paper, we address QRM-MLD (Maximum Likelihood Detection with QR Decomposition and M-algorithm) signal detection method for spatially multiplexed MIMO (Multiple Input Multiple Output) systems. Recently, the QRM-MLD signal detection method which can achieve 1Gbps transmission speed for next generation mobile communication was implemented in a MIMO testbed for the mobile moving at a pedestrian speed. In the paper, we propose a novel signal detection method 'reduced complexity QRM-MLD' that achieves identical error performance as the QRM-MLD while reducing the computational complexity significantly. We rigorously compare the two detection methods in terms of computational complexity to show the complexity reduction of the proposed method. We also perform a set of computer simulations to demonstrate that two detection methods achieve identical error performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7C
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• pp.616-626
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• 2007

In spatially multiplexed MIMO systems that enable high data rate transmission over wireless communication channels, the spatial demultiplexing at the receiver is a challenging task, and various demultiplexing methods have been developed recently by many researchers. Among the previous methods, maximum likelihood detection with QR decomposition and M-algorithm (QRM-MM)), and sphere decoding (SD) schemes have been reported to achieve a (near) maximum likelihood (ML) performance. In this paper, we propose a novel signal detection method that achieves a near ML performance in a computationally efficient manner. The proposed method is demonstrated via a set of computer simulations that the proposed method achieves a near ML performance while requiring a complexity that is comparable to that of the conventional MMSE-OSIC. We also show that the log likelihood ratio (LLR) values for all bits are obtained without additional calculation but as byproduct in the proposed detection method, while in the previous QRM-MLD, SD, additional computation is necessary after the hard decision for LLR calculation.

• Health Policy and Management
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• v.25 no.3
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• pp.240-251
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• 2015

Background: Dentist's income is quite variable. We investigate the factors underlying the distribution of dental revenue and dentist income. Methods: Financial and structural variables of private dental practices(N=13,967) were examined with 2010 Economic Census microdata which include non-insurance revenue. We conducted quantile regression method(QRM) and ordinary least square(OLS) in treating skewness and heteroskedasticity of distributions. The effective estimation for the upper and lower range of distribution becomes possible by QRM. Results: Mid-career dentists are shown to have higher revenue and income. Male dentists achieve the higher revenue and income than female dentists in all quantiles. Group practices show lower income per owner than solo practices significantly. The revenue and income are increased with increasing size of clinics. The high cost in renting the clinic office is found to have a big positive effect on the revenue but a little positive effect on the income. Interestingly the density of dentists shows negative effect on the lowest quantile of the revenue but positive effect on the highest quantile. The lowest quantile of the revenue in the capital areas have the relatively high revenue. The lowest quantile of the income in metropolitan city show higher income than those in other areas significantly. Conclusion: The suggested QRM is shown to have more effective and efficient tool in finding out determinants of dentists' revenue and income of our concern. The results of this study are expected to be employed for dentists preparing for the opening practices in their organizational settings and locational selections. The distributional efficiency of dental human resources could be accomplished if policy makers guide dentists with this knowledge.