인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
초록·키워드
In recent years, there has been increasing interest in applying multicarrier (MC) / code division multiple access (CDMA) system for wireless personal and multimedia communication applications. In this paper, we evaluate the performance of an OFDM/CDMA communication system in frequency domain using autoregressive(AR) modeling. Owing to AR modeling, the transmission channel can be modeled more close to the realistic mobile radio environment based on measured data and also we can save enormous simulation time. We assess the performances of the OFDM/CDMA system corresponding to the variation of SNR and the number of users. transversal filter(DTF). The response of the filter is resulted from the statistics of the measured amplitudes, delays, and phases of the multipath propagation. The taps of DTF are chosen to generate the recommended rms delay spread of a specific channel. Whereas, the frequency domain model is based on reproducing the frequency response of the channel. This model has been generated by an autoregressive(AR) process. The advantage of using the frequency domain model over time domain model is that the former uses fewer parameters and saves us considerable simulation time especially in the case of multicarrier system simulation. Many previous papers have evaluated the performance of OFDM/CDMA systems in Rayleigh or Rician fading channel. However, the trial of performance evaluation of an OFDM/CDMA system in a realistic channel condition has not been performed yet. In this paper, the transmission channel is modeled as AR process and more close to the realistic mobile radio environment based on measured data from Turin[9] and Suzuki[10]. We evaluate the performance of an OFDM/CDMA communication system in frequency domain using AR process corresponding to the variation of SNR and the number of users.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2009-569-013246781