Min-goo Kim

LTE-advanced modem design: challenges and perspectives

The commercial deployment of LTE Release 8 is gaining significant momentum all over the globe, and LTE is evolving to LTE-Advanced, which offers various new features to meet or exceed IMT-Advanced requirements. Since LTE-Advanced targets ambitious spectral efficiency and peak throughput, it poses tremendous system design challenges to operators and manufacturers, especially for mobile terminals. This article discusses modem design issues related to carrier aggregation, enhanced ICIC for HetNet, detection of eight-layer transmission, reference signals for enhanced multi-antenna support, and HARQ buffer management. We provide an overview of technical challenges and sketch the perspectives for tackling them to exploit the full benefits of the LTE-Advanced system.

Vulnerability indices for power systems

The purpose of vulnerability assessment is to determine when a disruption of service is likely to occur and to take steps to reduce the associated risk. With the growth of power systems, increases in grid complexity, and the trend toward deregulation, vulnerability assessment is imperative. Accurate vulnerability assessment is especially vital during heavy loading conditions and a vulnerability index is greatly needed to help the operator steer the system to viable conditions. In this paper, two new vulnerability assessment methods are proposed. One is based on the distance of the current operating point from the vulnerability border of the system. The other is an index based on the anticipated loss of load. These two methods are fully applicable to the case of cascading events

Feature reduction techniques for power system security assessment

Neural Networks (NN) have been applied to the security assessment of power systems and have shown great potential for predicting the security of large power systems. The curse of dimensionality states that the required size of the training set for accurate NN increases exponentially with the size of input dimension. Thus, an effective feature reduction technique is needed to reduce the dimensionality of the operating space and create a high correlation of input data with the decision space. This paper presents a new feature reduction technique for NN-based power system security assessment. The proposed feature reduction technique reduces the computational burden and the NN is rapidly trained to predict the security of power systems. The proposed feature reduction technique was implemented and tested on IEEE 50-generator, 145-bus system. Numerical results are presented to demonstrate the performance of the proposed feature reduction technique.