• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.48-58
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• 2012

New digital predistortion technique is proposed for power amplifier linearization in multi-band transmission systems. We consider a system where muli-band signals are combined and amplified by a single power amplifier (PA). In this system, the PA output is distorted by the nonlinear cross-products between different band signals as well as their own nonlinear self-products. To compensate these nonlinear effects, we propose a multiple PD structure. Each PD removes the nonlinear cross-products and self-products to mitigate the spectral regrowth for the corresponding band. Since the PD parameters for different bands are linked together, it is difficult to find the PD parameters separately. Thus, we propose an iterative method for finding the PD parameters jointly. For demonstration of the proposed method, multi-band characteristics of PA are extracted from a commercial power amplifier. Computer simulation was executed based on the PA parameters. The simulation results show that the proposed method can effectively linearize the PA and remove spectral regrowth at each signal band.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.487-492
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• 2017

Clustering is a technique which is used to measure similarities between data in big data analysis and data mining field. Among various clustering methods, k-Modes algorithm is representatively used for categorical data. To increase the performance of iterative-centric tasks such as k-Modes, a distributed and concurrent framework Spark has been received great attention recently because it overcomes the limitation of Hadoop. Spark provides an environment that can process large amount of data in main memory using the concept of abstract objects called RDD. Spark provides Mllib, a dedicated library for machine learning, but Mllib only includes k-means that can process only continuous data, so there is a limitation that categorical data processing is impossible. In this paper, we design RDD for k-Modes algorithm for categorical data clustering in spark environment and implement an algorithm that can operate effectively. Experiments show that the proposed algorithm increases linearly in the spark environment.