• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.6
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• pp.538-545
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• 2002

In the orthogonal frequency division multiplexing (OFDM) system, the nonlinear distortion in the high power amplifier(HPA) degrades the system performance because of the high peak-to-average power ratio (PAPR). In this paper, a semi-analytical method is newly proposed for the performance evaluation of the nonlinearly distorted OFDM communication system. In the proposed method, at first, the probability density function (pdf) of the PAPR is generated by computer simulation. Then, mean and variance of the non-linear distortion noise process are computed. Next, the overall BER is found by the analytical method. When the equivalent SSPA model is applied in case of the QPSK/16-QAM and AWGN channel, the BER is calculated for the variation of the IBO(input back-off) and PAPR parameter. It is shown that the results by proposed method are very similar to those of the conventional Monte-Carlo method. The computation time can be considerably reduced than the conventional method that depends on the magnitudes of BER and IBO.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.63-66
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• 1998

MC-CDMA(Multi-Carrier Code Division Multiple Access) 시스템에서 전송 신호의 피크 전력 대 평균 전력(Peak-to-Average Power: PAP)율을 낮추는 방안을 제시한다. 확산 코드에 의해 결정된 각 부 캐리어의 위상 오프셋은 전송 신호의 복소 포락선 형성에 영향을 주게 되어 전송 신호의 PAP 율을 결정하게 된다. 따라서 각 부 캐리어의 위상 오프셋을 적절히 조정함으로써 PAP율을 낮출수 있다. 본 논문에서는 PAP 율을 감소시키는 부 캐리어 위상 오프셋 코드의 한 예를 제시하며, 모의 실험을 통하여 전송신호의 크기 분포 특성과 PAP 율의 감소를 확인한다.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.435-438
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• 2008

우리나라 최대전력은 70년대 연도별로 36만 kW, 약 15%씩 증가하였으나, 최근 2000년대에는 연도별로 300만kW 이상, 약 6%대의 증가를 보이고 있다. 발생시간도 70년대에는 저녁시간대에 주로 발생했으나 80년대부터 최근까지는 15시에 하계 최대전력이 발생하고 있다 아울러 최근에는 기상의 변동폭 증가로 여름과 겨울의 계절성이 증폭되는 추세에 있고 이러한 최대전력 발생의 이면에는 시간별 부하패턴이 다양하게 나타나고 있다. 과거 70-80년대에는 연간이나 월간 부하패턴 모두 평균전력대비 변동폭이 크게 나타났으나 최근에는 변동폭이 상당히 작아지고 있다. 이는 최대전력에 못지않게 전력소비량이 지속적으로 증가하여 부하수준이 평준화되고, 부하율이 높아지고 있다는 것을 나타내며 연중 및 일간 피크 발생시점도 다변화되는 특징을 보이고 있다. 따라서 이러한 부하패턴 변화에 합리적으로 대응하기 위해서는 짧은 기간의 부하관리보다는 상시 수요관리인 효율향상 위주의 프로그램이 필요하고, 저렴한 전기 요금의 정상화를 통한 전력소비 감축을 통한 대응이 중요하다. 외국의 사례를 보면 우리나라 냉방 및 난방전력은 현재보다 10%p-20%p 정도 점유비가 추가적으로 상승할 개연성이 높으므로 다양한 시나리오 예측을 통한 철저한 위험관리 체계 확립이 요구된다.

• Journal of Navigation and Port Research
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• v.29 no.3 s.99
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• pp.245-250
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• 2005

In this paper, considering PAR of transmitter which is pointed out OFDM system's problem, we designed Coded OFDM (COFDM) system and estimated BER and SNR using PAR reduction method In order to evaluate performance, we compared M-ary PSK (M-ary Phase Shift Keying) with M-ary QAM (M-ary Quadrature Amplitude Modulation). In result, performance of 16-PSK and 16-QAM came to good Moreover, 16-QAM showed better performance of about 2 dB in 10-3 error probability and performance of about 5 dB in Peak power clipping than that of 16-PSK.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.26-32
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• 2014

Single-Carrier Frequency division multiplexing (SC-FDM) has been selected for the uplink transmission technique in 3GPP-LTE since it has an advantage of low peak-to-average power ratio (PAPR) in user's perspective. The receiver typically uses a frequency domain equalizer, which, however, suffers from noise boost and/or residual ISI especially when the channel has deep nulls. In this paper, we propose using turbo equalizer to mitigate such a problem. We provide link level performance comparison and an insight into how many iteration is needed for reasonable performance and complexity.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.2
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• pp.98-103
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• 2002

In case of power demand forecasting, the most important problems are to deal with the load of special-days. Accordingly, this paper presents the method that forecasting long (the Lunar New Year, the Full Moon Festival) and short(the Planting Trees Day, the Memorial Day, etc) special-days peak load using neural networks and regression models. long and short special-days peak load forecast by neural networks models uses pattern conversion ratio and four-order orthogonal polynomials regression models. There are using that special-days peak load data during ten years(1985∼1994). In the result of special-days peak load forecasting, forecasting % error shows good results as about 1 ∼2[%] both neural networks models and four-order orthogonal polynomials regression models. Besides, from the result of analysis of adjusted coefficient of determination and F-test, the significance of the are convinced four-order orthogonal polynomials regression models. When the neural networks models are compared with the four-order orthogonal polynomials regression models at a view of the results of special-days peak load forecasting, the neural networks models which uses pattern conversion ratio are more effective on forecasting long special-days peak load. On the other hand, in case of forecasting short special-days peak load, both are valid.