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This paper proposes a performance enhancement scheme using a coordinated multi-point (CoMP) with spatial phase coding (SPC) based on multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) in a heterogeneous network (HetNet) system. In the conventional system, the performance of the mobile terminal (MT) is degraded due to the inter-cell interference (ICI). When the MT is located on the cell edge, the performance and quality of service (QoS) of the MT are attenuated due to the interference caused by the signal transmitted from the adjacent base station (BS) or the signal broadcasted by other MTs. In order to increase the reliability of the MT, the proposed scheme uses a pre-coding and the CoMP scheme in HetNet. The proposed scheme can increase the signal-to-noise ratio (SNR) of the MT through the SPC scheme in the transmitter. Therefore, the proposed scheme can mitigate the performance degradation caused by the ICI and can enhance the reliability of the MT. The simulation results show that the proposed scheme has better bit error rate (BER) performance and has higher throughput than the conventional scheme. Therefore, the proposed scheme enhances the performance of the MT by using SPC with CoMP.

In this paper, an information theoretical approach to select features for speaker recognition systems is proposed. Conventional approaches having a fixed interval of analysis frames are not appropriate to represent dynamically varying characteristics of speech signals. To maximize the speakerrelated information varied by the characteristics of speech signals, we propose an information theory based feature selection method where features are selected to have minimum-redundancy with in selected features but maximumrelevancy to training speaker models.Experimental results verify that the proposed method reduces the error rates of speaker verification systems by 27.37 % in NIST 2002 database.

This research proposes new system which finds the music by using Query-by-Humming (QBH). For finding a stored music, the features of humming data are selected by using G.729 feature extractor. We normalize the extracted features by using mean-shifting, median filtering, average filtering and min-max scaling methods. Then the corresponding music is matched based on dynamic time warping (DTW) algorithm. As experiment, we compared the matching performance by using the database of Roger Jang's Corpus in MIREX.

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