• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.10
• /
• pp.4738-4758
• /
• 2017

Resource allocation plays a crucial role in multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems to improve overall system performance. While previously proposed resource allocation algorithms are mainly designed from the point of view of the information-theoretic, we formulate the resource allocation problem as an average bit error rate (BER) minimization problem subject to a total power constraint when considering employing realistic MIMO detection techniques. Subsequently, we derive the optimal subcarrier and power allocation algorithms for three types of well-known MIMO detectors, including the maximum likelihood (ML) detector, linear detectors, and successive interference cancellation (SIC) detectors. To reduce the complexity, we also propose a two-step suboptimal algorithm that separates subcarrier and power allocation for each detector. We also analyze the diversity gain of the proposed suboptimal algorithms for various MIMO detectors. Simulation results confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity. Moreover, it is shown that the suboptimal algorithms perform better than the conventional algorithms that are known in the literature.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.7
• /
• pp.72-85
• /
• 1998

In this paper, we propose a new method that sequentially estimates TDOA(Time Delay Of Arrival) and FDOA(Frequency Delay Of Arrival) for extracting the information about the bearing and relative velocity of a target in passive radar or sonar arrays. The objective is to efficiently estimate the TDOA and FDOA between two sensor signal measurements, corrupted by correlated Gaussian noise sources in an unknown way. The proposed method utilizes the one dimensional slice function of the third order cumulants between the two sensor measurements, by which the effect of correlated Gaussian measurement noises can be significantly suppressed for the estimation of TDOA. Because the proposed sequential algoritjhm uses the one dimensional complex ambiguity function based on the TDOA estimate from the first step, the amount of computations needed for accurate estimationof FDOA can be dramatically reduced, especially for the cases where high frequency resolution is required. It is demonstrated that the proposed algorithm outperforms existing TDOA/FDOA estimation algorithms based on the ML(maximum likelihood) criterionandthe complex ambiguity function of the third order cumulant as well, in the MSE(mean squared error) sense and computational burden. Various numerical resutls on the detection probability, MSE and the floatingpoint computational burden are presented via Monte-Carlo simulations for different types of noises, different lengths of data, and different signal-to-noise ratios.

• Journal of the Optical Society of Korea
• /
• v.17 no.6
• /
• pp.494-499
• /
• 2013

In this paper, we present an optical encryption and information authentication of 3D objects considering wireless channel characteristics. Using the optical encryption such as double random phase encryption (DRPE) and 3D integral imaging, a 3D scene with encryption can be transmitted. However, the wireless channel causes the noise and fading effects of the 3D transmitted encryption data. When the 3D encrypted data is transmitted via wireless channel, the information may be lost or distorted because there are a lot of factors such as channel noise, propagation fading, and so on. Thus, using digital modulation and maximum likelihood (ML) detection, the noise and fading effects are mitigated, and the encrypted data is estimated well at the receiver. In addition, using computational volumetric reconstruction of integral imaging and advanced correlation filters, the noise effects may be remedied and 3D information may be authenticated. To prove our method, we carry out an optical experiment for sensing 3D information and simulation for optical encryption with DRPE and authentication with a nonlinear correlation filter. To the best of our knowledge, this is the first report on optical encryption and information authentication of 3D objects considering the wireless channel characteristics.

• Journal of Korea Water Resources Association
• /
• v.34 no.4
• /
• pp.357-364
• /
• 2001

Sometimes the observed data is too small to discriminate it from noise of the instrument. Say, the data can be recorded as below DL(Detection Level) value. Even though the data below Detection Level(BDL) is small vague, it can be resulted in wrong estimates for mean and variance. However, in practice, the BDL data is generally eliminated as N.D. (Not Detected) and do not record it in Korea. This study investigates the distributions according to the data values of ammonia concentration (NH$_3$-N) in Puyeo intake. Also we try to find out DL value and an appropriate method for the estimations of mean and variance of BDL values that can be discriminate the distributions. The DL is estimated by trial and error method. The appropriate method for the estimations of mean and variance of above the detection level(ADL)and BDL dada sets is selected, and the mean and variance are estimated. As a result, it is found that the Bias Corrected Maximum Likelihood Estimator is the most accurate method for NH$_3$-N in Puyeo intake.

• Journal of Broadcast Engineering
• /
• v.5 no.2
• /
• pp.281-289
• /
• 2000

While acquiring images, the relative motion between the imaging device and the object scene seriously damages the image quality. This phenomenon is called motion blur. The peak-trace approach, which is our recent previous work, identifies important parameters to characterize the point spread function (PSF) of the blur, given only the blurred image itself. With the peak-trace approach the direction of the motion blur can be extracted regardless of the noise corruption and does not need much Processing time. In this paper stochastic peak-trace approaches are introduced. The erroneous data can be selected through the ML classification, and can be made small through weighting. Therefore the distortion of the direction in the low frequency region can be prevented. Using the linear prediction method, the irregular data are prohibited from being selected as the peak point. The detection of the second peak using the proposed moving average least mean (MALM) method is used in the Identification of the motion extent. The MALM method itself includes a noise removal process, so it is possible to extract the parameters even an environment of heavy noise. In the experiment, we could efficiently restore the degraded image using the information obtained by the proposed algorithm.